ALBERT

Description: 〈p〉Publication date: 15 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 252〈/p〉 〈p〉Author(s): Simone Baldi, Fan Zhang, Thuan Le Quang, Petr Endel, Ondrej Holub〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In smart buildings, the models used for energy management and those used for maintenance scheduling differ in scope and structure: while the models for energy management describe continuous states (energy, temperature), the models used for maintenance scheduling describe only a few discrete states (healthy/faulty equipment, and fault typology). In addition, models for energy management typically assume the Heating, Ventilation, and Air Conditioning (HVAC) equipment to be healthy, whereas the models for maintenance scheduling are rarely human-centric, i.e. they do not take possible human factors (e.g. discomfort) into account. As a result, it is very difficult to integrate energy management and maintenance scheduling strategies in an efficient way. In this work, a holistic framework for energy-aware and comfort-driven maintenance is proposed: energy management and maintenance scheduling are integrated in the same optimization framework. Continuous and discrete states are embedded as hybrid dynamics of the system, while considering both continuous controls (for energy management) and discrete controls (for maintenance scheduling). To account for the need to estimate the equipment efficiency online, the solution to the problem is addressed via an adaptive dual control formulation. We show, via a zone-boiler-radiator simulator, that the best economic cost of the system is achieved by active learning strategies, in which control interacts with estimation (dual control design).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Hannah Fontenot, Bing Dong〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper reviews the system components, modeling, and control of microgrids for future smart buildings in current literature. Microgrids are increasingly widely studied due to their reliability in the event of grid failure or emergency, their incorporation of renewable energy sources, and the potential they represent for overall cost reduction for the consumer. Greater accuracy in microgrid modeling enables the design of more advanced control methods, resulting in better objective optimization. This paper begins with an overview of microgrids and their components, their importance to both utility providers and building owners, and typical problems that they may be used to solve, as well as modeling challenges that microgrid researchers may face. An overview of microgrid control and optimization is given in terms of objectives, constraints, and optimization methods. Microgrid modeling is a complex task due to the number, variety, and complexity of microgrid components, which can include building loads, distributed energy resources, and energy storage systems. Various component modeling methods including physics-based and data-driven models are reviewed, to include battery degradation models. Furthermore, this paper provides a review of various data-driven forecasting methods for the microgrid controls. Different types of control methods including rule-based and model predictive control are reviewed, including latest occupancy-based model predictive control for buildings. Lastly, a discussion of current challenges that may be faced by researchers is presented, as well as future directions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 255〈/p〉 〈p〉Author(s): Yuecheng Li, Hongwen He, Amir Khajepour, Hong Wang, Jiankun Peng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Due to the high mileage and heavy load capabilities of hybrid commercial vehicles, energy management becomes crucial in improving their fuel economy. In this paper, terrain information is systematically integrated into the energy management strategy for a power-split hybrid electric bus based on a deep reinforcement learning approach: the deep deterministic policy gradient algorithm. Specially, this energy management method is improved and capable of searching optimal energy management strategies in a discrete-continuous hybrid action space, which, in this work, consists of two continuous actions for the engine and four discrete actions for powertrain mode selections. Additionally, a Critic network with dueling architecture and a pre-training stage ahead of the reinforcement learning process are combined for efficient strategy learning with the adopted algorithm. Assuming the current terrain information was available to the controller, the deep reinforcement learning based energy management strategy is trained and tested on different driving cycles and simulated terrains. Simulation results of the trained strategy show that reasonable energy allocation schemes and mode switching rules are learned simultaneously. Its fuel economy gap with the baseline strategy using dynamic programming is narrowed down to nearly 6.4% while reducing the times of engine starts by around 76%. Further comparisons also indicate approximately 2% promotion in fuel economy is contributed by the incorporation of terrain information in this learning-based energy management. The main contribution of this study is to explore the inclusion of terrain information in a learning-based energy management method that can deal with large hybrid action spaces.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 255〈/p〉 〈p〉Author(s): Marco Savino Piscitelli, Silvio Brandi, Alfonso Capozzoli〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The recent increasing spread of Advanced Metering Infrastructure (AMI) has enabled the collection of a huge amount of building related-data which can be exploited by both energy suppliers and users to gain insight on energy consumption patterns. In this context, data analytics-based methodologies can play a key role for performing advanced characterization, benchmarking and classification of buildings according to their typical energy use in the time domain. Traditionally, energy customers are classified according to their building end-use category. However, buildings belonging to the same category can exhibit very different energy patterns making ineffective this kind of a-priori categorization. For this reason, load profiling frameworks have been developed in the last decade to identify homogenous groups of buildings with similar daily energy profiles. The present study proposes a non-intrusive customer classification process, which does not use as predictive attributes in-field load monitoring data for the classification of unknown customers, but rather monthly energy bills and additional information on customers’ habits collected by means of a phone survey. The proposed classification process is developed by analysing hourly energy consumption data of 114 electrical customers of an Italian Energy Provider. The representative daily load profiles are grouped using the “Follow the Leader” clustering algorithm and a globally optimal decision tree is employed to build a supervised classification model. The model, compared to a baseline recursive partitioning tree, leads to an increase of accuracy of about 6%. Eventually, the procedure exploits energy bill data also for estimating the magnitude of typical load profiles.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 255〈/p〉 〈p〉Author(s): Quan Zhou, Ji Li, Bin Shuai, Huw Williams, Yinglong He, Ziyang Li, Hongming Xu, Fuwu Yan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The energy management system of an electrified vehicle is one of the most important supervisory control systems which manages the use of on-board energy resources. This paper researches a ‘model-free’ predictive energy management system for a connected electrified off-highway vehicle. A new reinforcement learning algorithm with the capability of ‘multi-step’ learning is proposed to enable the all-life-long online optimisation of the energy management control policy. Three multi-step learning strategies (Sum-to-Terminal, Average-to-Neighbour Recurrent-to-Terminal) are researched for the first time. Hardware-in-the-loop tests are carried out to examine the control functionality for real application of the proposed ‘model-free’ method. The results show that the proposed method can continuously improve the vehicle’s energy efficiency during the real-time hardware-in-the-loop test, which increased from the initial level of 34% to 44% after 5 h’ 35-step learning. Compared with a well-designed model-based predictive energy management control policy, the model-free predictive energy management method can increase the prediction horizon length by 71% (from 35 to 65 steps with 1 s interval in real-time computation) and can save energy by at least 7.8% for the same driving conditions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 255〈/p〉 〈p〉Author(s): Shiwei Xie, Zhijian Hu, Jueying Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The widespread utilization of electric vehicles has inspired the emerging trend of coupled transportation and distribution system, which entails the systematic methodologies to model the new planning problems. This paper proposes a scenario-based comprehensive expansion planning model for a coupled transportation and active distribution system. With the aim of minimizing the investment and operation costs, this model determines the best alternatives, locations and sizes for candidate assets, including traffic roads, distribution lines, distribution generators, capacitor banks, static var compensators, voltage regulators, energy storage systems and charging facilities, as well as their operation strategies. First, a generated scenario method is extended to incorporate the uncertainty of the traffic flow demand. Based on multiple scenarios, the steady-state distribution of traffic flow is characterized by the Wardrop user equilibrium principle, and the corresponding equivalent constraints are derived and incorporated into the model. For active distribution system, we formulate the operation constraints for related infrastructures. Considering the interdependency between the two systems, an expansion planning model is proposed, which simultaneously optimizes the investment and operation strategies. Due to the nonlinear nature of the model, we have developed a three-dimensional piecewise linear approximation and applied second order cone relaxation to reformulate the model as a mixed-integer second order conic program; thus, the global optimal solution can be found in a reasonable time frame. Results on a test system reveal that the variations of both systems have some influences on each other, indicating the significance of considering the interdependencies between transportation and active distribution system.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 255〈/p〉 〈p〉Author(s): Xiaokai Chen, Hao Lei, Rui Xiong, Weixiang Shen, Ruixin Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Open circuit voltage (OCV) has a considerable influence on the accuracy of battery state of charge (SOC) estimation. Three efforts have been made to reconstruct OCV for SOC estimation of lithium ion batteries in this study: (1) A new parameter backtracking strategy is proposed for online parameter identification using the recursive least square (RLS) algorithm to obtain stable OCV, which significantly reduces the jitters occurring in OCV identification results. (2) Historical experimental data of lithium ion batteries are used to derive baseline OCV curve and determine constraint boundaries, then an extended Kalman filter (EKF) is employed as a state observer to estimate the SOC for the same types of the batteries that have not been tested. (3) The OCV-SOC curve is reconstructed based on the accumulated online parameter identification and SOC estimation results. The OCV curve can be locally reconstructed even when the accumulated data only cover a partial range of SOC, which is suitable for electric vehicle (EV) operation conditions. Once the OCV curve is reconstructed, the response surface model of OCV-SOC-Capacity is applied to update battery capacity. In this way, the OCV curve can be gradually reconstructed from high SOC to low SOC during battery discharging process. The use of the reconstructed OCV curve to estimate SOC significantly improves the SOC estimation accuracy with the maximum error less than 3% for EV operation conditions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 255〈/p〉 〈p〉Author(s): Jucheng Xiao, Guangyu He, Huan Zhou, Siyuan Zhang, Zhihua Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With increasing renewable energy penetration and large capacity DC operation, there is a severe shortage of contingency reserve in the power system, which leads to the reduction of unit operational efficiency. In this paper, the concept of decentralized transfer of contingency reserve (DTCR) is firstly proposed. DTCR refers to the transfer of partial centralized contingency reserve from supply side to demand side for optimal decentralized distribution of contingency reserves in the overall system. DTCR scheme can enlarge the operation space of units and optimize the allocation of resources. Then, the benefit assessment model of DTCR is established, considering the impact of wind generators and demand response. Moreover, several important impacting factors on DTCR benefits are analyzed visually and mathematically. Thus, the diminishing marginal benefit (DMB) is found as an essential reference to select a suitable decentralized reserve capacity. The economic load rate threshold (ELRT) can be used to assess the degree of DTCR benefit and determine the operation conditions of DTCR scheme. Besides, this paper explains the benefit mechanism of DTCR, including the reduction of grid power loss and the optimized unit generation dispatch. Finally, DTCR benefits of 4 IEEE standard systems of 57 buses to 300 buses are assessed. Results indicate the significance of DTCR and verify the theoretical analysis of impacting factors and mechanism, as well as the usefulness of DMB and ELRT. DTCR is especially applicable in the peak load period for the system with insufficient contingency reserves. The work of this paper provides a new idea for alleviating the reserve burden and improving the economics of unit operation, as well as an important reference for DTCR planning, operation, and benefit allocation in the future.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Xiaoyi Ding, Xiaojing Lv, Yiwu Weng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The correlation between effectiveness of multiple operating parameters is a complicated issue and significant to the safe operation of solid oxide fuel cell/gas turbine (SOFC/GT) hybrid system. This paper presents a numerical analysis on biogas-fueled SOFC/GT hybrid system with a recirculation process using combustor exhaust gas. With consideration of safety constraints for critical components (fuel cell thermal crack, reformer carbon deposition, turbine blade overheat), the interaction mechanism of recirculation ratio, steam/carbon ratio and fuel/air ratio is studied from the perspective of thermodynamic analysis. Results show that the recirculation process could increase the electrical efficiency of system from 58.18% to 62.8%. However, for the safety consideration of SOFC, the acceptable recirculation ratio should be controlled between 0.17 and 0.32. Meanwhile, there exists a minimum point of turbine inlet temperature at the recirculation ratio of 0.3. With recirculation ratio switched from 0.1 to 0.3, impact of steam/carbon ratio variation on SOFC temperature gradient shrinks from 52.5% to 17.9% of the reference value. On the other hand, effect of fuel/air ratio variation on SOFC temperature gradient is promoted from 20.8% to 44.3% of the reference value, due to that oxidation reaction of biogas becomes a dominant factor. Based on these results, a parametric comparison is carried out to quantitatively describe the impact of recirculation process on the effectiveness of other parameters. Short discussion is conducted on parameter selection to acquire higher system efficiency and sufficient safety range, in which case the total output power of 176.8 kW and electrical efficiency of 61.78% could be achieved.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Yidian Zhang, Shaopeng Guo, Zhenyu Tian, Yawen Zhao, Yong Hao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Nanocatalysts of compound metal oxides (La〈sub〉2〈/sub〉CuO〈sub〉4〈/sub〉)〈sub〉x〈/sub〉(CNZ-1)〈sub〉1−x〈/sub〉 (x = 0.3, 0.5, 0.7) were prepared. Steam reforming of methanol (SRM) over these nanocatalysts was experimentally studied at a H〈sub〉2〈/sub〉O/methanol molar ratio of 1.6. The results showed that the methanol solution catalyzed by all catalysts synthesized in this work could be completely converted into H〈sub〉2〈/sub〉, CO〈sub〉2〈/sub〉 and a small amount of CO below a reaction temperature of 270 °C with a liquid hourly space velocity (LHSV) of 1.2 ml/(g·h). The catalysts of La〈sub〉2〈/sub〉CuO〈sub〉4〈/sub〉 and CuO/ZnO/Al〈sub〉2〈/sub〉O〈sub〉3〈/sub〉 were tested under the same operating conditions. Compared with La〈sub〉2〈/sub〉CuO〈sub〉4〈/sub〉, LCOx-CNZ showed better performance with a higher methanol conversion rate and H〈sub〉2〈/sub〉 yield. Conversely LCO5-CNZ had better CO and H〈sub〉2〈/sub〉 selectivity compared with CuO/ZnO/Al〈sub〉2〈/sub〉O〈sub〉3〈/sub〉. LCO3-CNZ showed good competitiveness in all four above aspects when operated at 150–270 °C. It could be concluded that LCOx-CNZ with special structures provided a significant improvement in catalytic performance of SRM benefiting from the synergistic effect among La〈sub〉2〈/sub〉CuO〈sub〉4〈/sub〉 and CuZnAl oxides. Thermodynamics analysis and experiments using a hybrid power generation system were applied with the above catalysts. Under direct normal irradiation at 915 W/m〈sup〉2〈/sup〉 and a reaction temperature of 230 °C, LCO3-CNZ showed 9.7% higher H〈sub〉2〈/sub〉 yield and 3.9% higher net solar power generation efficiency than did Cu/Zn/Al oxides.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Xiaolei Zhang, Longhua Hu, Michael A. Delichatsios, Jianping Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This work investigates the effects of the wall on the morphologic characteristics of non-premixed buoyancy driven turbulent flames attached to the wall. Experiments are carried out with rectangular burners having their long side attached to a wall. The investigation is based on dimensional analysis and comprehensive experimental data, including comparison of the flame characteristics of the wall attached flames with free flames. Results show that the non-dimensional flame heights of wall attached flames experience a two-dimensional to three-dimensional transition as free flames do. The critical dimensionless heat release rate for this transition is smaller for the wall attached flames (0.30) than that of the free flames (0.39). The flame height fluctuation of wall attached flames is smaller than that of free flames and decreases with an increase in the nozzle aspect ratio. The ratio of flame thickness (or flame width) to flame height of wall attached flames is smaller than that of free flames. New correlations for flame height, width and thickness of the wall attached flames are proposed based on the mirror-approach of the rectangular source relative to that of a free flame, where the burner perimeter is found to be an appropriate length scale. This work provides important knowledge on the effect of wall on flame characteristics of buoyancy driven turbulent flames, which is essential to the design and risk assessment of the laying of gaseous fuel transportation pipelines in the city and also provides data for validation of computational fluid dynamics (CFD) models.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Taskin Jamal, Craig Carter, Thomas Schmidt, G.M. Shafiullah, Martina Calais, Tania Urmee〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉One of the primary technical challenges of integrating high levels of PV generation into standalone off-grid power supply systems is their variable power output characteristics. In dealing with this issue, the integration of reliable PV forecasting techniques and preferably energy storage, are highly effective. Applying a short-term PV forecasting method, together with a compensatory controllable resource, can help in the management of system operation. This study incorporates the development of an energy flow modelling tool that has been used to analyse the benefits of 1-min ahead PV forecasting and battery storage for different system configurations. Based on the five days of 1-min ahead forecasting results analysed, it is found that PV forecasting enables the prosumer to install more than double the PV capacity, compared to the allowed installed PV capacity when no forecasting is employed. This additional PV capacity saves around 24–25% (on average) of diesel fuel per day for the diesel-PV-battery configuration. The outcomes evidently indicate that incorporating 1-min ahead PV forecasting enables a significant increase of PV hosting capacity of the system, without compromising the reliability of the system.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Jean-Laurent Duchaud, Gilles Notton, Alexis Fouilloy, Cyril Voyant〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉When sizing a renewable energy power plant in a grid-connected scenario, the optimal solution depends on the energy exchange rates between the actors of the electrical network. This study presents an optimization method that can be adapted to various power plant configurations to obtain the best size for each component, depending on the weather and the consumption. The optimization problem is solved in two steps. A Multi-Objective Particle Swarm Optimizer gives the trade-off between the cost of the components and the amount of non-renewable energy used, then the posttreatment takes into account the energy exchange tariffs and presents the solutions that minimize the production cost for any import and export rates. Those results can be used to evaluate the feasibility of an installation or to define the exchange tariffs with the grid regulation entity. This study also showcases the effect of the economic assumptions and of the choice of the energy management strategy on the optimal solution. The results show that the variation of the optimal production cost is limited but the component size has to be adapted accordingly. In the same way, the Energy Management Strategy used influences the plant design without affecting significantly the production cost.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Xingyu Liang, Bowen Zhao, Fei Zhang, Qingling Liu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Selective Catalytic Reduction (SCR) system provides an effective approach to removing NOx emission, in order to meet stringent emission legislation of NOx generated by internal combustion engine. However, the oversize SCR system would increase its operation costs and occupy more space, which restricts its widespread application to a certain extent. Therefore, the compact structure design of SCR system is worthy of research considering the limited installation space. In the present study, one-dimensional SCR model is established, and the effect of structural parameters on the SCR performance has been investigated by AVL BOOST. Then, based on the Response Surface Methodology (RSM), the coupling relationship among these structural parameters is explored. The optimal structural parameter values of SCR are calculated through the coupling relationship function. The SCR volume of the optimal structural parameters is reduced by 23.82% and the pressure drop generated by SCR reactor is reduced by 10.38%, which not only lead to the reduction of fuel consumption and also save the space and energy on ship. Meanwhile, and the NOx conversion is decreased slightly to 0.51%.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Siyuan Chen, Qi Zhang, Hailong Li, Benjamin Mclellan, Tiantian Zhang, Zhizhou Tan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Developing shallow geothermal energy is expected to play an important role to supply affordable, clean and reliable heating by many countries in the world. However, the development is mainly hindered by the high upfront investment costs and various risks involved in the exploration, construction and operation phases. The present study proposed a compound options model to explore the optimal investment timing and value based on the consideration of both investment and operational flexibilities. The Least Square Monte Carlo and Markov Chain Monte Carlo methods were employed in the model to find the solutions. A case study was carried out for China, and five scenarios were simulated to understand the effects of different policies including subsidy, carbon trading mechanism, preferential taxation and preferential electricity price. The obtained results show that, (i) the incentive policies are essential for the development of shallow geothermal energy, which can attract more investment before 2030; (ii) the government is suggested to carry out a preferential electricity price for shallow geothermal development, rather than increase the subsidy; (iii) the application of compound options method increases the investment value in all five scenarios, but its impact on investment timing varies.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Pucheng Pei, Dongfang Chen, Ziyao Wu, Peng Ren〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Lifetime evaluation and prediction is a key topic for proton exchange membrane (PEM) fuel cells, which can contribute to prolong the durability and accelerate the commercialization of fuel cells. In this paper, a linear formula to evaluate the maximum service lifetime of fuel cells for vehicle applications and several nonlinear formulas to predict the lifetime of fuel cells are presented. The terminal voltage of fuel cells at the rated condition is defined as the average cell voltage decreasing by ca. 10% from the start rated voltage at the rated condition. A nonlinear formula based on the variation of the hydrogen crossover is derived, which reveals that the variation of the hydrogen crossover is the main factor for the nonlinear lifetime degradation of fuel cells. The nonlinear formula based on the time response of first-order control systems (FOCS) for the overall process is proposed, and the segment point between linear and nonlinear degradation is also defined by this formula. Then a more accurate segmented formula with linear lifetime formula and nonlinear lifetime formula based on the time response of FOCSs for the local process is derived. Finally, the segmented formula is verified by experiment results of the single cell and fuel cell stacks and practical operating results of fuel cell vehicles. Moreover, methods for lifetime evaluation in the laboratory and online prediction in the vehicle are proposed.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Linjun Li, Shixue Wang, Like Yue, Guozhuo Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The key to successfully cold starting proton-exchange membrane fuel cells is increasing the cell temperature above 0 °C before the electrochemical reaction stops, because ice forms in fuel cells below this temperature. To decrease the input of external heat energy to fuel cells during cold starting, this paper proposes a local-heating method to improve the cold-start performance of fuel cells. During the experiments, heating wires were placed under partial ridges in the cathode plate to improve the cold-start performance of the fuel cells. The cold-start characteristics of the locally heated fuel cells were analyzed by measuring the voltage, high-frequency impedance, and cathode (gas diffusion layer) temperature for different heating power densities and number of heating wires. The results show that locally heating the cathode improves the cold-start capability of the fuel cell, and increasing the heating power density to heat the fuel cell enhances the voltage stability during cold starting of the cell. Furthermore, at a constant heating power density, the fuel cell using one heating wire shows better cold-start performance than that heated using three heating wires.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉 〈p〉Local heating apparently improves the cold-start ability of the fuel cell; the greater the local heating power, the faster the temperature of the reaction zone increases; the fuel cell using one heating wire showed better cold-start performance than that using three heating wires.〈/p〉 〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919314035-ga1.jpg" width="500" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Jufeng Yang, Yingfeng Cai, Chaofeng Pan, Chris Mi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A constant-current constant-voltage (CCCV) charge protocol is commonly used for lithium-ion batteries. The dynamic characteristic of the constant-voltage (CV) charging current is discovered to be related to battery aging. In order to quantitatively describe the load current during the CV charging period, an equivalent circuit model (ECM) based on the resistor-inductor (RL) network is proposed in this paper. Motivated by the current expression derived based on the conventional resistor–capacitor (RC) network-based ECM, an RL network-based ECM is developed to characterize the CV charging current. Then, the parallel-connected RL networks are employed to improve the model fidelity. The test data of four lithium iron phosphate (LiFePO〈sub〉4〈/sub〉) batteries in different aging states are employed to validate the proposed model. Comparative results show that the proposed 2nd-order ECM is the best choice, considering both the model accuracy and complexity. In addition, a simplified 2nd-order model is proposed, achieving a satisfactory accuracy with only three model parameters to be identified. Therefore, this model can be easily implemented in the battery management system (BMS).〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919314138-ga1.jpg" width="318" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Changzhao Jiang, Matthew C. Parker, Daniel Butcher, Adrian Spencer, Colin P. Garner, Jerome Helie〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents a comparative study of two injectors designed for the same Gasoline Turbocharged Direct Injection engine, one featuring 5 holes and one with 6 holes. Hole diameter and circumferential spacing also differed between the two injectors in order to optimise targeting while maintaining flow rate and drop size distribution. By comparing the macroscopic spray characteristics of the two injectors, this study investigated possible design features which may better maintain a spray’s intended morphology under severe flash boiling conditions. The sprays of each injector were firstly investigated by imaging in a quiescent pressure vessel before also being imaged in an endoscopically accessed version of the target 3-cylinder downsized engine to understand the impact of the spray morphology on performance and emissions. Near field images from the pressure vessel indicated that the 5-hole injector could tolerate a greater superheated degree before experiencing spray collapse, maintain its intended morphology better and exhibited a wider plume and shorter penetration length than the 6-hole injector for a given condition. Endoscopic images from the engine indicated that the spray area of the 5-hole injector was always wider under a range of start of injection timings, leading to a better air-fuel mixture and the observation of less diffusive combustion. The PN (particulate) emissions of the 5-hole injector was also consistently lower than the 6-hole injector under different injection timings due to better mixing and less piston impingement, whilst also being less sensitive to changes of injection timing due to its ability to maintain its spray morphology.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Ahinoam Pollack, Tapan Mukerji〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉It has been estimated that Enhanced Geothermal Systems could supply 100 GWe (10%) of total electric capacity in the U.S. An Enhanced Geothermal System (EGS) is created by stimulating an impermeable hot rock, injecting cold water into the hot reservoir, and extracting the heated water to generate electricity. EGS projects are still not commercially feasible, however, due to many challenges, including subsurface uncertainty. There are many uncertain structural and geological features when creating an EGS. With uncertain reservoir properties, it is difficult to optimize decisions that will greatly improve EGS profitability. Currently, a common method of optimizing an EGS is choosing the most representative subsurface reservoir model and optimizing the engineering parameters for this single reservoir model, or Single-Model Optimization (SM-Opt). Due to availability of larger computational power, another feasible option is accounting for subsurface uncertainty by optimizing an EGS given an ensemble of reservoir models, or Multiple Model Optimization (MM-Opt). This option is less common in practice within the geothermal industry since it lags in harnessing computational power. This study compares these two methods for optimizing eight common EGS engineering decisions, including well configuration and fracture spacing. The decisions were optimized to maximize the Net Present Value (NPV) of an EGS. We have found that using SM-Opt, the optimal engineering decisions led to an EGS with a NPV estimate of $32.7 million. This contrasts with the MM-Opt results where the optimal engineering decisions led to a median NPV value of $11 million and a standard deviation of $15 million. This comparison illustrates how ignoring subsurface uncertainty and heterogeneity leads to over-optimistic NPV forecasts. For this study, the SM-Opt optimum decisions were similar to the robust decisions identified using MM-Opt. Yet, in contrast to SM-Opt, the MM-Opt workflow provided an analysis of the influential engineering parameters and a NPV uncertainty range, which was used to ensure decision robustness.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Jan-Philipp Sasse, Evelina Trutnevyte〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Decentralized renewable electricity generation (DREG) has been growing at an unprecedented pace, yet the appropriate spatial allocation and associated regional equity implications remain underinvestigated. In this study, we quantify the trade-offs between cost-efficient (least-cost) and regionally equitable DREG allocation in terms of electricity generation costs, investment needs, and DREG capacity requirements. Using the case of the ambitious and publicly-approved Swiss Energy Strategy 2050, we set up a bottom-up, technology-rich electricity system model EXPANSE with Modeling to Generate Alternatives at a spatial resolution of 2’258 Swiss municipalities. In order to measure regional equity implication, we adapt the concepts of the Lorenz curve and the Gini coefficient. We find a significant trade-off by 2035 in Switzerland: 50% increase in regional equity when allocating DREG to various Swiss regions on the basis of population or electricity demand leads to 18% higher electricity generation costs. Least-cost allocation implies concentrating DREG and associated investments to few most productive locations only. Solar PV is the key technology for increasing regional equity. We conclude that in countries with spatially-uneven DREG resources like Switzerland, any policies that focus on cost efficiency should anticipate regional equity implications in advance and, if desired, minimize them by promoting solar PV.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919314114-ga1.jpg" width="419" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Jérémie Léger, Daniel R. Rousse, Stéphane Lassue〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉It is well known that indoor heat distribution can affect energy consumption according to the thermal comfort of the occupants. While most work on this topic has focused on specific heaters and how they distribute heat, this paper proposes a new concept termed virtual heaters. Virtual heaters are a set of two optimized heat distributors that respectively maximize and minimize the energy consumption inside a room while maintaining the same level of thermal comfort. The maximum and minimum virtual heaters are then applied in a comparison with a real heater tested in a specific room at constant thermal comfort in order to quantify its ability to provide comfort while using a minimum amount of energy. To calculate the ”virtual heaters”, a simplified heat transfer model is formulated and implemented. A volumetric thermal comfort model using the predicted mean vote is also discussed and used. The ”simplified” heat transfer model with the thermal comfort constraint is then optimized via a sequential quadratic programming algorithm. The proposed method is applied to the heating of a room subject to an outdoor temperature of 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si18.svg"〉〈mrow〉〈mo linebreak="badbreak"〉-〈/mo〉〈mn〉20〈/mn〉〈mspace width="0.25em"〉〈/mspace〉〈mi〉°〈/mi〉〈mi mathvariant="normal"〉C〈/mi〉〈/mrow〉〈/math〉 and compared to experimental results. Results show that the maximum virtual heater consumes approximately 35% more energy than the minimum virtual heater for the case considered herein.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Haozhong Huang, Delin Lv, Yingjie Chen, Jizhen Zhu, Zhaojun Zhu, Mingzhang Pan, Yajuan Chen, Wenwen Teng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Aromatics and cycloalkanes which play important roles in soot formation, are two important components in diesel. This work constructed a reduced multi-component mechanism of 〈em〉n〈/em〉-heptane–〈em〉n〈/em〉-butylbenzene (BBZ)– methylcyclohexane (MCH)–polycyclic aromatic hydrocarbon (PAH) with 183 species and 777 reactions for diesel engine emissions and combustion prediction. Based on the reduced mechanism of 〈em〉n〈/em〉-heptane–BBZ–PAH, this multi-component diesel mechanism was constructed by merging the reduced mechanism of MCH. First, the detailed mechanism of MCH was reduced based on the methods of direct relation graph with error propagation (DRGEP), sensitivity analysis, and rate of production (ROP) analysis. Next, some most important parameters of kinetics in the mechanism were optimized by sensitivity analysis method. Further, the simplified multi-component diesel mechanism was extensively validated using the experimental values of ignition delays, species concentrations, and laminar flame speeds. The developed mechanism provides favorable prediction results, indicating that it can be used for simulating the combustion of multiple components in diesel. Finally, the developed multi-component diesel mechanism was coupled with three-dimensional computational fluid dynamic (3D-CFD), and multidimensional numerical simulations were performed in a direct-injection compression ignition (DICI) engine at EGR = 0%, 13%, 27%, 37%. The prediction results well coincided with the experimental values of combustion characteristics and emissions of soot and NOx, indicating that this multi-component diesel mechanism could be applied for predicting practical engine simulations.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Dmitrii Bogdanov, Alla Toktarova, Christian Breyer〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transition towards 100% renewable energy supply is a challenging aim for many regions in the world. Even in regions with excellent availability of wind and solar resources, such factors as limited availability of flexible renewable energy resources, low flexibility of demand, and high seasonality of energy supply and demand can impede the transition. All these factors can be found for the case of Kazakhstan, a mostly steppe country with harsh continental climate conditions and an energy intensive economy dominated by fossil fuels. Results of the simulation using the LUT Energy System Transition modelling tool show that even under these conditions, the power and heat supply system of Kazakhstan can transition towards 100% renewable energy by 2050. A renewable-based electricity only system will be lower in cost than the existing fossil-based system, with levelised cost of electricity of 54 €/MWh in 2050. The heat system transition requires installation of substantial storage capacities to compensate for seasonal heat demand variations. Electrical heating will become the main source of heat for both district and individual heating sectors with heat cost of about 45 €/MWh and electricity cost of around 56 €/MWh for integrated sectors in 2050. According to these results, transition towards a 100% renewable power and heat supply system is technically feasible and economically viable even in countries with harsh climatic conditions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Ramato Ashu Tufa, Ylenia Noviello, Gianluca Di Profio, Francesca Macedonio, Aamer Ali, Enrico Drioli, Enrica Fontananova, Karel Bouzek, Efrem Curcio〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although desalination market is today dominated by Seawater Reverse Osmosis (SWRO), important technological issues remain unaddressed, specifically: relatively low water recovery factor (around 50%) and consequent huge amount of brine discharged, and energy consumption (3–5 kWh/m〈sup〉3〈/sup〉) still far from the minimum thermodynamic value (∼1 kWh/m〈sup〉3〈/sup〉). Herein, the energy performance of an innovative systems combining SWRO, Membrane Distillation (MD) and Reverse Electrodialysis (RED) for simultaneous production of water and energy is investigated. The valorization of hypersaline waste brine by Salinity Gradient Power production via RED and the achievement of high recovery factors (since MD is not limited by osmotic phenomena) represent a step forward to the practical implementation of Zero Liquid Discharge and low-energy desalination. The analysis is supported by lab-scale experimental tests carried out on MD and RED over a broad set of operational conditions. Among the different case studies investigated, exergetic efficiency reached 49% for the best scenario, i.e. MD feed temperature of 60 °C, MD brine concentration of 5 M NaCl, RED power density of 2.2 W/m〈sup〉2〈/sup〉MP (MP: membrane pair). Compared to the benchmark flowsheet (only SWRO), up to 23% reduction in electrical energy consumption and 16.6% decrease in specific energy consumption were achieved when including a RED unit. The analysis also indicates that optimization of thermal energy input at the MD stage is critical, although it can potentially be fulfilled by low-grade waste heat or solar-thermal renewable sources. Overall, the proposed integrated system is coherent with the emergent paradigm of Circular Economy and the logic of Process Intensification.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Philippe Gentillon, Siddharth Singh, Suhas Lakshman, Zhaolun Zhang, Appu Paduthol, N.J. Ekins-Daukes, Qing N. Chan, Robert A. Taylor〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The high temperatures of combustion systems make them suitable for coupling with thermophotovoltaic systems. In practice, it is quite challenging to reduce heat losses and the spectral mismatch between the emission of the combustion source and the spectral response of photovoltaic (PV) cells. In an effort to pull these disparate energy-focussed research fields together, this paper explores the use of a low-cost erbia (Er〈sub〉2〈/sub〉O〈sub〉3〈/sub〉) coating on a novel porous media combustion-based thermophotovoltaic (PMC-TPV) reactor for continuous combined heat and power generation. In this work, three different configurations were analysed, including a non-coated porous foam, a coated porous foam, and a coated quartz container. As such, this study provides the first in-depth analysis and characterisation of all salient components of a PMC-TPV system. It includes a detailed characterisation of a 24-cell gallium antimonide (GaSb) array, which was attached to a heat sink and used to harvest the radiant emission from a hot (〉1200 °C), yttria-stabilised zirconia/alumina composite (YZA) ceramic foam. Since the ceramic foam does not have an ideal emissivity curve for these cells, the ability of the erbia coating to control the spectral emission was measured. The results show that by applying the erbia coating to the outer surface of the YZA foam (e.g. using a simple 2-step process of dip coating followed by curing/calcination), it is possible to increase performance, achieving a maximum in-band emission fraction of 25.4% at a firing rate of 1300 kW/m〈sup〉2〈/sup〉 (i.e. around 10% of increase than that for non-coated configuration), which provides a temperature of 1285 °C. Additionally, a maximum power output of 1 W was achieved by using erbia coating on YZA foam. For the third configuration, the use of the erbia coating on the quartz tube (instead of the YZA foam) leads to an increase in the maximum core temperature of the reactor up to 1443 °C; however, this also leads to a decrease in electrical performance due to a lower in-band fraction. These findings show that applying an erbia coating on an industrial radiant emitter could enable a combined heat and power processes to gain around 30% increase of electrical output. Finally, since the PV fill factor was lower than expected, and electroluminescence measurements indicated cell damage, these findings also reveal the importance of continuously monitoring PV parameters in PMC-TPV systems.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Minho Kim, Huiyong Chun, Jungsoo Kim, Kwangrae Kim, Jungwook Yu, Taegyun Kim, Soohee Han〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Lithium-ion batteries have been used in many applications owing to their high energy density and rechargeability. It is very important to monitor the internal physical parameters of the lithium-ion battery for safe and efficient usage, because this can help estimate the state of the battery, develop battery aging models, and schedule optimal operation of batteries. Parameter optimization methods using an accurate electrochemical battery model are much less expensive than direct parameter measurement methods, such as post-mortem methods. Thus, many model-based parameter optimization methods have been developed so far. However, most of these methods are random search methods that are based on heuristic rules, which leads to data-inefficient parameter identification. This means that they require many time-consuming battery model simulation runs to identify optimal parameters. Herein, a novel learning-based method is proposed for data-efficient parameter identification of lithium-ion batteries. A deep Bayesian neural network is used to efficiently identify optimal parameters. The simulations and experimental data validation show that the proposed method requires much fewer battery model simulation runs to identify optimal parameters than existing methods such as genetic algorithms, particle swarm optimization, and the Levenberg-Marquardt algorithm. The parameter estimation error of the proposed method is about 10 times lower than that of the second-best algorithm.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): M. Pagani, W. Korosec, N. Chokani, R.S. Abhari〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The transition to electric mobility is accelerating, and, thus it is increasingly important to be able to anticipate and adapt future development of the electric vehicle charging infrastructure. A novel agent-based simulation framework coupled with a detailed geo-referenced digital model of the built infrastructure is developed and applied. The charging behaviour of individual electric vehicle users as well as the spatial distributions of electric vehicles are accounted for in the simulation framework. More than 2500 scenarios of the transition to electric mobility in a mid-size city in Switzerland are assessed. The time to break-even of the electric vehicle charging infrastructure is up to 50% shorter when users are charged on the basis of parking fees rather than power sales. However, the revenues from parking fees are shown to be more sensitive to the behaviours and preferences of the users. At today’s low penetrations of electric vehicles, the profitability of the charging infrastructure is very uncertain, and thus entrants into the marketplace will have substantial financial exposure until the penetrations are of order 10%. Additionally, it is shown that, at specific transformers, public charging considerably increases grid loads by up to 78% during peak hours; these local increases, rather than the average city-wide increase in load, are the critical determinant of the required upgrades to the distribution grid. Overall, this novel simulation framework facilitates the planning of electric vehicle charging infrastructure that will support a successful transition to electric mobility.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Nick Eleftheroglou, Sina Sharif Mansouri, Theodoros Loutas, Petros Karvelis, George Georgoulas, George Nikolakopoulos, Dimitrios Zarouchas〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the discharge voltage is utilized as a critical indicator towards the probabilistic estimation of the Remaining Useful Life until the End-of-Discharge of the Lithium-Polymer batteries of unmanned aerial vehicles. Several discharge voltage histories obtained during actual flights constitute the in-house developed training dataset. Three data-driven prognostic methodologies are presented based on state-of-the-art as well as innovative mathematical models i.e. Gradient Boosted Trees, Bayesian Neural Networks and Non-Homogeneous Hidden Semi Markov Models. The training and testing process of all models is described in detail. Remaining Useful Life prognostics in unseen data are obtained from all three methodologies. Beyond the mean estimates, the uncertainty associated with the point predictions is quantified and upper/lower confidence bounds are also provided. The Remaining Useful Life prognostics during six random flights starting from fully charged batteries are presented, discussed and the pros and cons of each methodology are highlighted. Several special metrics are utilized to assess the performance of the prognostic algorithms and conclusions are drawn regarding their prognostic capabilities and potential.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): P. Singh, N. Déparrois, K.G. Burra, S. Bhattacharya, A.K. Gupta〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉High-temperature gasification is an attractive alternative technology for clean energy production from plastic wastes and provides a sustainable pathway for their disposal. Waste cross-linked polyethylene (XLPE) offers good potential energy recovery source because of its high energy density of around 47 MJ/kg that can be converted to syngas using pyrolysis or gasification. CO〈sub〉2〈/sub〉 assisted gasification can provide clean and efficient syngas that can be converted further to valuable products. This can effectively decrease the carbon foot-print from the utilization of polyethylene wastes. This paper examines pyrolysis and CO〈sub〉2〈/sub〉 assisted gasification of XLPE waste with focus on the kinetics, product yield and syngas yield properties (yield of carbon monoxide, hydrogen, and hydrocarbon) at different temperatures. Pyrolysis experiments were carried out to estimate the impact of the gasifying agent over pyrolysis. Pyrolysis and CO〈sub〉2〈/sub〉 assisted gasification were conducted at several temperatures in the range 973 K to 1173 K in steps of 50 K. The results were compared with high-, medium-, low-density polyethylene as well as ultra-high molecular weight polyethylene. Higher temperatures provided increased syngas yields from pyrolysis. The activation energy of pyrolysis from single-step kinetic analysis of TGA data revealed increases with an increase in branching and cross-linking. The reaction profiles of the single step of all the samples (except medium density polyethylene) were found to be closely represented by the Avrami-Erofeev models. Results also revealed that gasification generated more syngas, hydrogen, and energy than pyrolysis. Gasification consumed the CO〈sub〉2〈/sub〉 to generate syngas with a mass-specific heating value similar to natural gas suggesting efficient utilization of both CO〈sub〉2〈/sub〉 and XLPEs for clean and efficient energy production.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Shaojian Wang, Jieyu Wang, Chuanglin Fang, Kuishuang Feng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study estimates disparities in carbon intensity in China using a multi-scalar and multi-mechanism analysis. In order to avoid the inconsistency between regional, provincial, and city-level data, city-level CO〈sub〉2〈/sub〉 emissions from energy consumption in China were estimated through Defense Meteorological Satellite Program/Operational Linescan System nighttime light imagery. Our results reveal a trend of decreasing inequality in carbon intensity in China, and the study also found that the contribution made by eastern China to that inequality decreased continuously, while the share of inequality in western China increased consistently during the study period. Spatial Markov chains were also applied to identify the spatiotemporal dynamics of inequalities in Chinese cities. The results show that there is a strong effect of the emission status of neighboring cities’ on a city’s emission dynamics and the effect of self-reinforcing agglomeration was significant. Based on a multi-level model, the study further revealed that the disparity in China’s carbon intensity levels was sensitive to the regional hierarchy across a variety of mechanisms acting as potential influencing factors. We found that technological progress and population density have a potential to mitigate the intensities driven by economic development, trade openness, road density, secondary industry proportion, and investment intensity. Through the present study, we argue that the policies targeting emissions mitigation in China have been restrained due to a lack of effective restraint in relation to the influencing factors that have promoted emissions levels, while mitigation factors have not been adequately exploited.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Xian Li, Alexander Lin, Chin-Huai Young, Yanjun Dai, Chi-Hwa Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Net-zero energy buildings are playing a critical role in the decarbonization of future cities since the buildings are responsible for 30–40% of total energy consumption. A residential net-zero energy building with a prospect of commercialization was introduced, which adopts solar energy systems and heat insulation solar glass that simultaneously generates electric power and minimizes heat loss. Dynamic and parametric simulation models were developed based on the TRNSYS platform and were validated by experimental data or standard test reports. A multi-criteria decision-making framework based on the energetic and economic criteria was developed to evaluate system performance and to find the favorable layout of the energy system in the residential net-zero energy building. Twelve system scenarios, covering the individual heat insulation solar glass system, the hybrid systems integrated with solar PV, solar thermal and heat insulation solar glass, and the hybrid systems combined solar thermal and heat insulation solar glass, were comparatively assessed. Among the system scenarios inclusive of solar thermal technology, a combination of the compound parabolic concentrated solar collector and variable-effect absorption chiller is highly recommended. However, the system scenario, which consists of a specific PV area of 8.4 m〈sup〉2〈/sup〉/kW and employs heat insulation solar glass, is most favorable due to a highest primary energy saving ratio of 1.05 and a lowest levelized total cost of 5920 US$/year. All system scenarios proposed herein are not economically feasible at the current economic parameters in Singapore’s climate. However, the optimized hybrid system (integrated with solar PV, solar thermal and heat insulation solar glass) is sufficient to reach the net-zero energy target while the optimized solar PV system combined heat insulation solar glass is a solution of the positive energy building.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphic abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313960-ga1.jpg" width="279" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Shihui Ma, Jia-nan Zheng, Dawei Tang, Xin Lv, Qingping Li, Mingjun Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Marine natural gas hydrate production has become a hot topic in recent years. There is still a long way to achieve the commercial production of marine hydrate reservoirs. The purpose of this work is to investigate the natural gas hydrate decomposition characteristics in the real marine sediments obtained from the South China Sea. A high-pressure micro-differential scanning calorimeter was employed to study the thermodynamic properties of natural gas hydrates. The results indicated that the increase in gas pressure or sediment salinity decreased the ice melting temperature by changing the vapor pressure of water. In addition, the decrease in sediment moisture from 40% to 30% increased the decomposition pressure of hydrates by 4.4 MPa at 278 K of sea bottom temperature, due to the water absorption capacity of the sediments increases the actual salinity furtherly. The influence of mixed gases on the decomposition pressure of hydrates was also investigated. The findings of this work on the effects of salinity and gas components on the decomposition pressure are significant to the spot safety production of marine natural gas hydrate reservoirs.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313406-ga1.jpg" width="269" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Y. Zhang, C.Y. Tso, J.S. Iñigo, S. Liu, H. Miyazaki, Christopher Y.H. Chao, K.M. Yu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Windows are one of the most inefficient components in buildings. Common thermochromic smart windows using VO〈sub〉2〈/sub〉 can mitigate such energy loss. However, they suffer from several problems, namely, low solar modulation ability, high transition temperature (i.e. 68 °C) and low luminous transmittance. In this study, we propose a perovskite thermochromic smart window towards achieving high solar modulation ability whilst maintaining a high luminous transmittance and a low transition temperature. Perovskite material shows a significant thermochromism in the visible and ultraviolet region. Since half of the photons lie in this spectral region, a high solar modulation can be achieved by perovskites. The material was optimized by varying the spin speed in the fabrication process as well as the mixing ratio between precursors. The optimized sample exhibits a solar modulation ability of 25.5% with luminous transmittance of 34.3% and higher than 85% in the hot (80 °C) and cold (25 °C) states, respectively, making this material suitable for practical device applications. The hysteresis loop, the transition temperature as well as transition time in relation to the relative humidity of a perovskite smart window during the heating and cooling process are investigated in this study. From field tests results, the perovskite smart window can help reduce the indoor air temperature by about 2.5 °C compared to a normal window. Overall, based on the results obtained in this study, the perovskite thermochromic smart window has potential to achieve excellent thermochromic properties, providing an alternative to alleviate the high energy consumed in buildings.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313777-ga1.jpg" width="372" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Zhenyuan Yin, Li Huang, Praveen Linga〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Methane hydrates have been considered as the future clean energy resource. To recover energy from hydrate-bearing sediments safely and effectively requires a fundamental understanding of the dynamic behaviour of hydrates in sandy media. Past field production tests have proved the technical feasibility of gas production from hydrate reservoirs. However, technical challenges (e.g. sand production and excessive water production) remain in realizing long-term economic-viable production. In this study, we investigate the effect of various wellbore designs (specifically the shape and the location of perforations) on the fluid production behaviour in aqueous-rich hydrate-bearing sediments. Slotted-liner design was first-time incorporated in depressurization under different bottom-hole pressures (2.5 MPa, 3.0 MPa and 4.0 MPa). Continuous gas production and step-wise water production during the early stage of depressurization were observed at all pressures because of the change of fluid flow path from reservoir to wellbore. Compared with traditional borehole design, slotted-liner design showed advantage in controlling water production under low BHP (2.5 MPa). Using wellbores with different perforation locations, it was observed that perforation location does not pose a significant impact on the behaviour of gas production; whereas, middle perforation away from the aqueous-rich and hydrate-rich region yielded the least water production. The experimental results from this study demonstrated the possibility of employing slotted-liner well and varying the perforation location in reducing water production from methane hydrate-bearing sediments. Our findings can pave way for the testing of novel wellbore designs to further enhance gas recovery and reduce water production from hydrate reservoirs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Wanlin Gao, Tuantuan Zhou, Yanshan Gao, Qiang Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With the increasing concerns on fossil fuel depletion, environment deterioration, and global warming, great efforts have been devoted to the concept of “hydrogen economy” and the mitigation of CO〈sub〉2〈/sub〉 emission. Among different technologies, enhanced water gas shift processes have exhibited significant importance not only for the production of high purity H〈sub〉2〈/sub〉 but also for their efficient CO〈sub〉2〈/sub〉 separtion. By highlighting the novel materials and practical applications, we present a state-of-art review on the enhanced water gas shift processes towards improved CO〈sub〉2〈/sub〉 removal and H〈sub〉2〈/sub〉 production via Le Chatelier’s principle. First, we discussed detailed utilization of membrane reactors based on assortments of H〈sub〉2〈/sub〉-permselective membranes with a particular emphasis on their advantages and weaknesses towards CO〈sub〉2〈/sub〉 separation. We also introduced the unique development of solid CO〈sub〉2〈/sub〉 adsorbents, followed by their potential applications for intermediate-CO〈sub〉2〈/sub〉 capture. Furthermore, the integrated combination of membrane assisted/sorption enhanced WGS processes are featured in this promising field. Finally, we critically reviewed recent implementations and applications with challenges and outlooks on the basis of the current development.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S030626191931387X-ga1.jpg" width="322" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Wonjae Choi, Jaehyun Kim, Yongtae Kim, Han Ho Song〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A solid oxide fuel cell (SOFC)–internal combustion engine (ICE) hybrid system is a recently-proposed distributed electric power generation system to achieave extremely high efficiency beyond that of current technologies. The objectives of this study are to find the operation characteristics of the SOFC in the hybrid system and determine the operational design point of the hybrid system. To accomplish these objectives, operation of a 5 kW-class SOFC–ICE hybrid system was analysed by integrating the experimental results of the internal combustion engine with the simulation models of other system components. Two unique characteristics of SOFC operation were found and analysed. First, the SOFC in the hybrid system should utilize anode inlet gas with low temperature (e.g., 750–800 K) and low external reforming rate (e.g., 30–40%), which decreases the SOFC temperature, especially at the entrance, where the current density becomes very low, decreasing SOFC performance. Second, the overall effects of pressure pulsation caused by the engine on SOFC operation are insignificant since the flow path between the SOFC and the engine acts as a damper, reducing the pressure pulsation amplitude. The estimated variations were 0.2 mV in SOFC cell voltage. To determine the operational design point of the hybrid system, parametric analyses of system operation were conducted while varying several control parameters, e.g., SOFC fuel utilization factor. The design point of system operation was determined by considering system performance and operational stability. Near-zero pollutant emissions and 59.0% system efficiency were achieved at the determined design point, a 7.9% absolute and 15.5% relative improvement compared to that of an SOFC stand-alone system.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉 〈p〉The design point performance of the SOFC–internal combustion engine hybrid system.〈/p〉 〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313686-ga1.jpg" width="500" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Hudson Bolsoni Carminati, Raquel de Freitas D. Milão, José Luiz de Medeiros, Ofélia de Queiroz F. Araújo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sugarcane plantations promote impressive drainage of atmospheric carbon dioxide reaching 781 t/h for a 1000 t/h sugarcane-biorefinery. For first-generation bioethanol sugarcane-biorefineries, only 10% of sugarcane carbon dioxide equivalent leaves as hydrous-ethanol, while 90% return to atmosphere through bagasse-fired power cogeneration in steam-Rankine cycles. Thus, a sugarcane-biorefinery exports two bioenergy flows – electricity and hydrous-ethanol – and its impressive Bioenergy Carbon Capture and Storage potential is wasted. Capture of fermentation carbon dioxide merely means 5% of Bioenergy Carbon Capture and Storage efficiency. This work assesses a new sugarcane-biorefinery concept dramatically raising the Bioenergy Carbon Capture and Storage efficiency. With fermentation carbon dioxide already captured, it is advocated to implement 90% post-combustion capture of flue-gas carbon dioxide. Then, captured carbon dioxide is compressed and traded as Enhanced Oil Recovery agent transported to deep-water offshore oil fields via high-pressure pipelines counting on topographic gravitational effects to lower compression power. Aggregating pipeline/compression investment to the biorefinery, it is shown that such new Plantation-Biorefinery-Post-Combustion-Pipeline-Oil-Recovery enterprise is technically feasible for 5.22 MtCO〈sub〉2〈/sub〉/y of Bioenergy Carbon Capture and Storage capacity and is economically feasible under certain conditions: (i) idle pipeline capacity rental to fossil carbon emitters at 10–20 USD/tCO〈sub〉2〈/sub〉; (ii) recovered oil revenues traded at 1–2 bbl/tCO〈sub〉2〈/sub〉 and 50–80 USD/bbl; (iii) carbon-taxation at 40–80 USD/tCO〈sub〉2〈/sub〉; and (iv) carbon Cap-and-Trade at 30–70 USD/tCO〈sub〉2〈/sub〉. Under such conditions the Plantation-Biorefinery-Post-Combustion-Pipeline-Oil-Recovery can attain 7 MMMUSD net value and 6 years payback-time.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313200-ga1.jpg" width="500" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Tom Terlouw, Tarek AlSkaif, Christian Bauer, Wilfried van Sark〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Residential demand profiles typically demonstrate a mismatch between energy demand and PV supply. Different solutions are proposed, such as demand side management and energy storage systems. Nevertheless, costs and environmental impacts of some technologies (e.g. batteries) are high. This paper proposes two system designs: Home Energy Storage (HES) and Community Energy Storage (CES). Besides electricity storage, heat storage is used in the two system designs to supply domestic hot water and space heating. Furthermore, the trade-offs between the different storage mediums in relation to costs are analyzed. To achieve that, different methodologies are used to size the electricity and heat storage mediums for HES and CES. Next, a multi-objective mixed integer linear programming model is developed to optimize the operation costs and 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si86.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi mathvariant="normal"〉CO〈/mi〉〈/mrow〉〈mrow〉〈mn〉2〈/mn〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉-emissions for each system design. After that, the model is tested on a residential community situated in Cernier (Switzerland). The results demonstrate that CES performs better than HES on economic and environmental performance due to economies of scale and the optimally sized storage capacity of the battery in CES. Currently, none of the proposed system designs is economically feasible. However, the sensitivity analysis shows that a profitable system design can be obtained for both HES and CES, when the electricity storage (i.e. battery storage) size is reduced and the heat storage (i.e. water storage tank) size is increased.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Xinyi Li, Ziliang Zhu, Zirui Xu, Ting Ma, Hao Zhang, Jun Liu, Xian Wang, Qiuwang Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Latent heat thermal energy storage with metal foams has been considered as a promising candidate for thermal management in aerospace systems. Thus, there is good cause to deeply explore the heat transfer mechanisms of phase change material (PCM) melting with metal foams. In order to get close to the real situation, a three-dimensional, pore-scale lattice Boltzmann model is explored based on a three-dimensional reconstructed porous structure morphology taken from experimentally observed in this paper, to characterize the distribution of flow and temperature fields during charging of porous PCM. The gravity effects on heat transfer performance are documented by comparison of charging at different accelerates. During the charging process, nonuniform temperature distributions and inclined melting interfaces are presented at the latter stages, caused by the interplay of primary natural convection in the melting direction and secondary convection in the transverse direction. More inclined melting interfaces are observed as gravitational acceleration increases, yielding faster PCM melting in the upper region while melting in the bottom region almost terminated. This implies that natural convection gradually dominates heat transfer and leads to the temperature nonuniformity. Similar shape characteristics of melting interface are observed in two-dimensional model, while there is an apparent difference of the melting fraction, showing it gradually growing from 4.1% to 8.6% with increasing gravitational acceleration. These results indicate that secondary convection effect neglected in the two-dimensional model, leading to a significant error in the prediction of heat transfer performance.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Ruiyuan Zhang, Ting Min, Li Chen, Qinjun Kang, Ya-Ling He, Wen-Quan Tao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Understanding catalyst degradation mechanisms and their effects on reactive transport in proton exchange membrane fuel cell (PEMFC) is critical for prolonging cell lifetime. In this study, for the first time pore-scale numerical studies are conducted to explore effects of catalyst degradation on transport and electrochemical reactions in catalyst layers (CLs) of PEMFCs. High-resolution nanoscale structures of pristine and degraded CLs are reconstructed, in which detailed distributions of carbon, Pt, electrolyte and pores are resolved. Different particle size distributions of Pt agglomerates are also considered during the reconstruction. Based on the lattice Boltzmann method, pore-scale models for oxygen diffusion, interfacial dissolution, and electrochemical reaction are developed. Pore-scale modeling is then conducted to evaluate effects of Pt degradation on Pt utilization, active surface area, limiting current density and local transport resistance. It is found that total reaction rate is reduced by approximately 10–30% due to Pt degradation. Such negative effects are more prominent when Pt loading is low or more Pt is distributed in the CL interior, causing 25% and 45% increased transport resistance, respectively. Further, a multi-scale simulation strategy is proposed, and upscaling schemes for integrating pore-scale results into cell-scale models are proposed. The present study demonstrates that pore-scale simulation is a useful tool for understanding coupled mechanisms between Pt degradation and reactive transport phenomena within CLs, and is helpful for providing practical guidance for CL fabrication.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312644-ga1.jpg" width="310" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Bo Jiang, Haifeng Dai, Xuezhe Wei, Tianjiao Xu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Accurate and reliable estimation of battery state of charge (SOC) and capacity is essential for the management of the lithium-ion battery in electric vehicles. In this paper, a novel joint estimation approach of battery SOC and capacity with an adaptive variable multi-timescale framework is proposed, which also deals with the interference of current measurement offset (CMO) effectively. Aiming at the problem of unknown CMO, which will affect the accuracy of battery modeling and state estimation, an original two-stage recursive least squares algorithm is raised to identify the battery model parameters and the CMO quickly. The adaptive extended Kalman filter is applied to improve the SOC estimation accuracy by updating the noise covariance adaptively, and the recursive total least squares is used to estimate capacity with the consideration that both the battery SOC estimation and charge accumulation suffer from noises. Finally, a joint estimation of SOC and capacity structure is founded, and to address the issue of different varying characteristics of battery SOC and capacity, a novel adaptive variable multi-timescale framework is proposed. The experimental results indicate the accuracy, convergence, and adaptivity of the proposed method in different working conditions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Peyman Fasahati, Wenzhao Wu, Christos T. Maravelias〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, we develop, synthesize, and evaluate a cyanobacteria biorefinery incorporating all relevant subsystems including: (1) supply of CO〈sub〉2〈/sub〉, water, and nutrients, (2) production at cultivation ponds, and (3) products separation and purification. A superstructure-based approach is proposed to evaluate technical and economic feasibility of cyanobacteria biorefineries to produce biochemicals. Supply subsystems include a wastewater treatment (WWT) facility and a power plant to provide water, nutrients, and CO〈sub〉2〈/sub〉. In the production subsystem, an approach to model cultivation ponds is developed based on production requirements and cyanobacteria characteristics i.e. residence time and productivity. In the purification subsystem, optimal separation technologies are selected based on product attributes and concentration to recover products and recycle water and nutrients, while minimizing costs. Later, all subsystems are integrated and system-wide optimization is performed. Impacts of key parameters such as cyanobacteria productivity and performance for a cellular level analysis; and CO〈sub〉2〈/sub〉 transportation phase, distances, and product titers for a systems level analysis are investigated. Results indicate that depending on product attributes, the production cost could vary between $2.74−$34/kg ($0.7−$2.65/kg) at product concentrations of 0.5 g/L (10 g/L), highlighting the importance of achieving higher product titers. Analyses for the base-case show that for a titer of 0.5 g/L, reducing productivity from 30 to 5 g m〈sup〉−2〈/sup〉 day〈sup〉−1〈/sup〉 while increasing residence time from 5 to 30 days increases the production cost by about 22% in the system with water and nutrients supply form WWT, respectively. Results show that providing water and nutrients from a WWT facility improves the economics. The present study provides critical insights for future research and development and successful commercialization of cyanobacteria biorefineries.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312991-ga1.jpg" width="422" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Ian J. Scott, Pedro M.S. Carvalho, Audun Botterud, Carlos A. Silva〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Decision makers rely on models to make important regulatory, policy, and investment decisions. For power systems, these models must capture (i) the future challenges introduced by the integration of large quantities of variable renewable energy sources and (ii) the role that energy storage technologies should play. In this paper, we explore several different approaches to selecting representative days for generation expansion planning models, focusing on capturing these dynamics. Further, we propose a new methodology for adjusting the outputs of clustering algorithms that provides three advantages: the targeted level of net demand is captured, the underlying net demand shapes that define ramping challenges are accurately represented, and the relationship between annual energy and peak demand is captured. This weighting methodology reduces the magnitude of the error in the representative day based generation expansion planning models estimation of costs by 61% on average. The results also demonstrate the importance of carefully performing the clustering of representative days for both system costs and technology mix. In most cases improvements to the total cost of different representative day based expansion plans are realised where conventional generation capacity is substituted for energy storage. Based on the energy storage technology selected we conclude this capacity is being used to address ramping challenges as opposed to shifting renewable generation from off to on peak periods, reinforcing the importance of capturing detailed intraday dynamics in the representative day selection process.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 256〈/p〉 〈p〉Author(s): Masood S. Alivand, Omid Mazaheri, Yue Wu, Geoffrey W. Stevens, Colin A. Scholes, Kathryn A. Mumford〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The energy penalty is a primary limitation for the implementation of the aqueous solvents for large-scale post-combustion CO〈sub〉2〈/sub〉 capture processes. In this study, a novel aqueous-based phase change solvent, composed of potassium glycinate (GlyK, reactive species), water (H〈sub〉2〈/sub〉O, solvent) and dimethylformamide (DMF, antisolvent) was developed to improve the energy efficiency of CO〈sub〉2〈/sub〉 capture. To examine the role of the antisolvent, a series of aqueous-based amino acid solvents (GlyK-X) with different DMF:H〈sub〉2〈/sub〉O (X) volume ratios was prepared, fully characterized and assessed. It was observed that a CO〈sub〉2〈/sub〉-free phase appeared at the top of the aqueous-based amino acid GlyK-X solvents after CO〈sub〉2〈/sub〉 absorption which can be easily separated and recycled to the absorption column and save energy. The results showed that the GlyK-60 solvent with DMF:H〈sub〉2〈/sub〉O volume ratio of 60:40 had a very high CO〈sub〉2〈/sub〉-free phase volume (63%). Moreover, the GlyK-60 solvent exhibited 26.1% (0.433–0.546 mol CO〈sub〉2〈/sub〉/mol GlyK) enhancement in CO〈sub〉2〈/sub〉 absorption capacity, 38.5% (130–80 min) decrease in regeneration time and 59.1% reduction in relative heat duty compared to the conventional aqueous GlyK solvent. Overall, the outcomes confirmed that the aqueous-based phase change GlyK-60 solvent is a viable solvent option for large-scale CO〈sub〉2〈/sub〉 capture with extra-low energy consumption and a key to the success of Paris Climate Accord.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919315983-ga1.jpg" width="266" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 256〈/p〉 〈p〉Author(s): Chun Wang, Ruixin Yang, Quanqing Yu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In order to avoid the sharps and transients of power demand and extend the battery lifetime, three energy management strategies via wavelet transform (WT) considering temperature uncertainty for hybrid energy storage system (HESS) in the plug-in hybrid electric vehicle are proposed in this paper. The HESS consisting of batteries, ultracapacitors, along with two associated DC/DC converters is discussed and modeled in details. In addition, to further investigate the influence of temperature uncertainty, a random temperature variation and three-dimensional response surfaces are employed for modeling. To systematically compare the performances of WT-based (WTB) strategy, WT-and-rule-based (WTRB) strategy and WT-and fuzzy-logic-control-based (WTFLCB) strategy, an optimization scheme is presented directly. The simulation results demonstrate that the WTFLCB strategy shows better performance under temperature uncertainty. Moreover, a hardware in the loop experiment platform is set up to further verify the feasibility of the WTRB strategy for actual application. It is found that the battery SoC and ultracapacitor SoC estimation errors are less than 0.77% and 3.87%, respectively.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): L.B. Zhang, H.L. Dai, A. Abdelkefi, S.X. Lin, L. Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Extracting energy from environmental airflows and converting it into usable electricity can be a potential approach to realize the self-powering operation of sensors by virtue of energy harvesting technology, which has received great interest in recent years. Yet the environmental adaptability and the level of output power are two of important aspects to restrict wide applications of energy harvesters and hence still required to be improved. For this purpose, a novel and efficient electromagnetic energy harvester for airflow power generation is designed, and a theoretical model is constructed and experimentally verified to characterize the design and output performance of the energy harvester. To this end, a bluff body with the cross-section of Y-shape subjected to airflows is considered. Then, the aeroelastic response of bluff body occurs and brings the coil to cut magnetic induction lines. The experimental results show that an average power of 2.5 mW is measured at wind speed of 4 m/s, which is dominant compared to existing aeroelastic energy harvesters. Furthermore, charging and discharging experiments demonstrate 30 s of airflow in wind tunnel under speed of 3.5 m/s can drive the sensor of 1.1 V working voltage to operate for about one minute. In addition, it is significant that the harvester’s environmental adaptability is revealed under condition of the air-conditioner vent. The present research offers a suggestive guidance on developing an efficient electromagnetic energy harvester for airflow power generation, at the same time it further promotes the realization of self-powering of structural health monitoring sensors applying in buildings and bridges.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Rongsen Jin, Peng Hou, Guangya Yang, Yuanhang Qi, Cong Chen, Zhe Chen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Offshore wind power plants have been considered as one of the fastest-growing types of renewable energy technologies that is superior to the onshore wind farms with low impacts on habitat, better wind condition, higher energy efficiency, etc. The cost of submarine cables takes a significant proportion of the overall capital cost for a large-scale offshore wind farm, rendering the task of optimization of electrical infrastructure a critical role in modern wind farm design. With the increasing capacity and offshore distance, the impact of power losses in the cables on the economic performance of the wind farm becomes significant. Therefore, both the investment on the cables and the cost from the associated energy loss need to be considered in the optimization model. In this work, a detailed power loss cost model accounting for the wake effect’s impact on the wind turbine output is proposed. The cable cost and the associated power losses cost are considered in the objective function. The offshore substation location, cable connection layout, and cable sectional area are optimized simultaneously while ensuring an uncrossed cable connection layout via a line segment intersection detection algorithm. Due to the non-convexity of the optimization model, an adaptive particle swarm optimization algorithm is adopted. The proposed method was validated through a case of a real offshore wind farm, where the simulation results show that the cable connection layout formulation and sectional area selection varies significantly when different power loss model is applied. A 3.14% total cost reduction can be achieved by using the proposed method compared with the case without the power loss model.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): A. Gurubalan, M.P. Maiya, Patrick J. Geoghegan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Air conditioning (AC) systems demand a significant portion of the total energy consumed by the building sector. Conventional AC based on vapor compression refrigeration (VCR) is neither energy efficient nor environment-friendly due to its method of humidity control and use of refrigerants with global warming potential respectively. Liquid desiccant air conditioning system (LDAS) is a promising alternative to VCR. This review provides a comprehensive overview of the developments in LDAS so far. It explains the principle of operation and classification in detail. The various developments in dehumidifier, regenerator, desiccant material, and mathematical modelling are discussed. The various types of performance parameters, and the design criteria and effect of operating parameters are also detailed. Finally, the climate feasibility, performance control strategies and indoor air quality are explained. This communication will be useful to identify the research gaps to explore new pathways for future research to further improve the efficiency of LDAS.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Giulia Ulpiani〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉For the first time, a systematic review was conducted on mist spraying systems used for outdoor cooling by perusing twenty years of publications from 12 countries and 7 climatic zones. The twofold aim was to emphasize both the potential against local overheating in a variety of climatic contexts and the extreme heterogeneity in terms of investigation techniques and performance metrics that hinder the construction of a cohesive body of knowledge. In addition to statistics and patterns, data were screened to outline theoretical and methodological trends and gaps and to detect geographic biases and climate dependencies. Indeed, each study was thoroughly described and comparatively discussed according to (i) the investigational method (purely experimental studies, purely numerical studies and those combining field tests with simulations), (ii) the results in terms of cooling, humidification and comfort, also in relation to the adopted performance metrics (iii) the design novelty. Most relevant approaches and findings were discussed and compared to identify governing variables, optimized configurations, unchartered solutions and criticalities. Overall, the collected data qualify water spraying as a cost-effective, versatile and high-impact blue mitigator. Opportunities and challenges towards an informed use emerged and will help delineating appropriate guidelines for practitioners involved in town development, to deliver strategies and precautions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Cristina Prieto, Luisa F. Cabeza〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Concentrated solar power (CSP) is today recognized as a unique renewable energy for electricity generation due to its capability to provide dispatchable electricity incorporating thermal energy storage (TES). Molten salts TES is the most widespread technology in commercial CSP but the industry is looking for cheaper and more efficient TES systems and phase change materials (PCM) have been highlighted as potential low cost and high energy TES systems. This paper presents a completely new concept of PCM energy storage systems to be used in solar thermal electricity plants with its technical assessment. A cascade type PCM storage system is evaluated, using four buckets with the PCM organized based on melting temperature and the latent energy of the materials. Daily, monthly, and annual transient simulations of the plant performance are carried out. The main conclusion is the similarity between this new concept and the commercial two-tank indirect molten salt system. The cumulative power production over the year is similar and the net production of both systems is well matched.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Christoph J. Meinrenken, Ali Mehmani〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Demand-side management (DSM) in response to market-based electricity tariffs can potentially increase the efficiency and reliability of the electric power grid. This study introduces a novel, one-day-ahead DSM framework which optimizes temperature setpoints and battery dispatch in office buildings, subject to a time-varying and/or demand-based electricity tariff. To reflect real world implementation, our framework operates in two-steps. First, during the passive, battery-only DSM optimization, historical weather and electricity load data for a given building are used to determine its optimal battery capacity. Second, once the battery has been installed, a one-day-ahead, real-time DSM algorithm optimizes both the building’s daily temperature setpoints and the battery's charge/discharge pattern. The optimization objective is to minimize the total operating cost (tariff charges and battery system) while still satisfying occupants’ thermal comfort. Using a case study with a medium-fidelity electric load model for a standard office building, the performance of the proposed framework is validated by quantifying savings in operating cost, reduction of monthly grid peak loads, and the achieved human occupant comfort. To illustrate the advantage of optimizing temperature setpoints and battery dispatch concurrently, the combined performance is compared with that achieved by standalone DSM (i.e., using only battery dispatch or only temperature setpoints). We found that concurrent optimization can reduce a building's monthly peak demand on the grid by up to 26%. Electricity tariff charges are reduced by 11%, more than is required to offset storage costs, thus providing an overall profit to building operators who use such DSM. Payback time is approximately 5 years.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Boris Brigljević, Jay J. Liu, Hankwon Lim〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Marine macroalgae or seaweeds are increasingly becoming strong candidates for sustainable biofuel feedstocks of the future. This study features a large-scale process design and comprehensive analysis of an industrial-scale (400,000 tons dry feedstock per year) poly-generation pyrolysis process that utilizes 3rd generation biofuel feedstock, 〈em〉Saccharina japonica〈/em〉 brown seaweed, and produces diesel-range hydrocarbon fuel, heat, and power. Process design relied predominately on published experimental data regarding fast pyrolysis of 〈em〉S. japonica〈/em〉 in a fixed-bed reactor system, followed by dewatering and catalytic upgrading of the produced biocrude. The design featured acid wash pretreatment for the reduction of mineral content, and subsequently a Rankine power cycle utilizing biochar. The design also considered two distinct cases of on-site hydrogen production and hydrogen purchase. Based on the experimental data, a rigorous steady-state flowsheet model was constructed using Aspen Plus for each design case. The results of comprehensive techno-economic assessment, sensitivity, and Monte Carlo analyses provided insight into capital cost for the process, minimum product selling price, and selling price ranges. Finally, the process is compared with traditional crude oil extraction and processing in terms of significant reductions in CO〈sub〉2〈/sub〉 emissions, hence providing strong evidence of its environmental sustainability.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313911-ga1.jpg" width="255" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Yiju Ma, Donald Azuatalam, Thomas Power, Archie C. Chapman, Gregor Verbič〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Battery storage, particularly residential battery storage coupled with rooftop photovoltaics (PV), is emerging as an essential component of the smart grid technology mix. However, including battery storage and other flexible resources like electric vehicles and loads with thermal inertia into a probabilistic analysis based on Monte Carlo (MC) simulation is challenging, because their operational profiles are determined by computationally intensive optimization. Additionally, MC analysis requires a large pool of statistically-representative demand profiles to sample from. As a result, the analysis of the network impact of PV-battery systems has attracted little attention in the existing literature. To fill these knowledge gaps, this paper proposes a novel probabilistic framework to study the impact of PV-battery systems on low-voltage distribution networks. Specifically, the framework incorporates home energy management (HEM) operational decisions within the MC time series power flow analysis. First, using available smart meter data, we use a Bayesian nonparametric model to generate statistically-representative synthetic demand and PV profiles. Second, a policy function approximation that emulates battery scheduling decisions is used to make the simulation of optimization-based HEM feasible within the MC framework. The efficacy of our method is demonstrated on three representative low-voltage feeders, where the computation time to execute our MC framework is 5% of that when using explicit optimization methods in each MC sample. The assessment results show that uncoordinated battery scheduling has a limited beneficial impact, which is against the conjecture that batteries will serendipitously mitigate the technical problems induced by PV generation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Maciej Mikulski, Praveen Ramanujam Balakrishnan, Jacek Hunicz〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Dual-fuel reactivity controlled compression ignition combustion offers potentially superior overall efficiency and ultra-low nitrogen oxides and soot emissions. Using natural gas as the low reactivity fuel also provides high knock-resistance and carbon dioxide emission reduction. However, the concept suffers from relatively low combustion efficiency at low engine loads, causing unacceptable methane slip. This study tackles this issue, applying numerical simulations to investigate the application of negative valve overlap to improve combustion efficiency of reactivity controlled compression ignition at low engine loads. The objective is modification of in-cylinder thermal and chemical state before combustion, by varying timing and amount of fuel injected directly into the recompressed hot exhaust gases. The study uses TNO's multi-zone, chemical kinetics-based combustion model with variable valve actuation functionality. The simulation is based on two experimentally validated cases: an uncooled exhaust gas recirculation strategy and a lean burn concept. In both cases, negative valve overlap elevates in-cylinder temperature and cuts methane emissions by 15%, without combustion optimization. Crucially, it enables peak exhaust recompression temperatures above 850 K, sufficient for diesel reforming/oxidation. The lean RCCI strategy takes greater advantage of fuel reforming than the exhaust gas recirculation case. Optimum conditions give almost 99% combustion efficiency and ultra-low methane emissions. Net indicated efficiency is 40.5% (@15% load), despite negative valve overlap’s substantial pumping losses. Low-load net efficiency is 5.5 percentage points above the lean strategy baseline and 3 pp. better than the exhaust gas recirculation baseline. This strategy is considered applicable on state-of-the-art dual-fuel gas engines without hardware changes.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Dengcheng Liu, Rui Lin, Bowen Feng, Lihang Han, Yu Zhang, Meng Ni, Sai Wu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Polymer electrolyte membrane fuel cells are promising power sources for vehicle and other portable applications due to their high energy efficiency and zero pollution emission during operation. To improve the performance and reliability of polymer electrolyte membrane fuel cells, effective and accurate diagnostic tools are urgently needed for polymer electrolyte membrane fuel cells practical applications. Different from the previous diagnostic methods that may damage the fuel cell structure, a novel interference-free diagnostic system based on the printed circuit board is proposed in this study. Fuel cell localised electrochemical impedance spectroscopy at different current density is observed. It is found that the activation impedance near inlet decreases sharply when current density increase. In addition, it is also found the flooding problem and the mass transport problem can occur at a medium current density due to the non-uniform behaviour of the polymer electrolyte membrane fuel cells. The proposed diagnostic system is demonstrated to be an effective tool to improve efficiency and robust of polymer electrolyte membrane fuel cells.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313996-ga1.jpg" width="354" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Tea Zakula, Marina Bagaric, Nenad Ferdelji, Bojan Milovanovic, Sasa Mudrinic, Katia Ritosa〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In 2017, the ISO 52016-1:2017 standard introduced a new methodology for the assessment of the building energy performance as a replacement for the simplified method used in the ISO 13790:2008 standard. The capabilities of the new standard have been considerably improved with respect to those of the old standard, but currently there is a lack of analyses that assess the accuracy and limitations of the new standard applied to realistic multi-zone buildings of various types and in various climates. This paper presents a comprehensive analysis of the model accuracy for a wide range of building uses, envelope properties, climates, and heating/cooling needs, ranging from 5 kWh/m〈sup〉2〈/sup〉 to 216 kWh/m〈sup〉2〈/sup〉 for heating and from 23 kWh/m〈sup〉2〈/sup〉 to 170 kWh/m〈sup〉2〈/sup〉 for cooling. The analysis was done by comparing the results from the ISO 52016-1:2017 standard with the dynamic simulation model in TRNSYS. The differences between the two methods in the annual energy needs are up to 40% for heating and up to 18% for cooling. Furthermore, it is shown that the use of constant values of solar energy transmittance and the overall heat transfer coefficient for windows can cause substantial errors in the calculation of building energy needs, more so for buildings with high-performance windows. Although a certain level of discrepancy between the ISO 52016-1:2017 standard and TRNSYS also occurs in the calculation of heat transfer through opaque elements, the differences seem to be less pronounced than for windows.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Seungpil Lee, Sungjun Yoon, Hyuckmo Kwon, Joonkyu Lee, Sungwook Park〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper describes the effects of swirl flow in a diesel optical single-cylinder engine with experimental results and simulation results obtained using KIVA code. Experiments were conducted with an optical single-cylinder engine for various operating conditions such as injection timing, exhaust gas recirculation (EGR), and swirl ratio, and a numerical study was also conducted to analyze the effects of swirl flow and combustion characteristics in detail. Correlations between in-cylinder flow from numerical simulations and the flame propagation process from experiments were conducted. The optical experimental and simulation results demonstrated that retarded injection timing and high EGR rate reduced the luminosity of flame and the wall heat transfer. However, a high EGR rate simultaneously reduced the combustion efficiency. The average luminosity of the optical image was determined by the flame in the high-temperature region above 2400 K. The luminosity and volume fraction of the temperature region above 2400 K showed the same trends. Correlation results between the experiment and simulation showed that swirl flow affects the propagation process. The flame region was generated in the center of the combustion chamber due to swirl flow based on visualization and analysis results. That is, swirl flow caused separation of the flame by disrupting the continuity of the spray.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313297-ga1.jpg" width="291" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): G.F. Frate, P. Cherubini, C. Tacconelli, A. Micangeli, L. Ferrari, U. Desideri〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Wind power fluctuations are typical of small size wind farms and may be a limiting factor in isolated small-size systems. An electric storage can be used to mitigate these fluctuations and enable the use of wind energy to provide energy to remote communities or microgrids. This study compares the performance of Li-Ion batteries and flywheels in abating the ramp rates of the power produced by a wind turbine. Production data was generated from actual wind measurements over one year. The capability of ramp abatement by varying storage capacity, power rating and ramp rate thresholds was investigated. The storage technologies were compared from the technical and economic point of views by means of a multi-objective optimization approach that showed the optimal trade-off between abatement capability and costs. The costs of storage periodic replacement, due to the degradation induced by a cycling operation, was also estimated. Results suggest that the abetment of wind power ramps up to 80% can be done at a relatively low price (between 5 and 10 k€). In this case flywheels outperform batteries in term of cost. If a higher abatement effectiveness is required (around 90%) the storage cost quickly increases. In this case the battery outperforms the flywheel and provide the same performance at much lower cost. If strict requirements are assumed, i.e. maximum permitted fluctuations are lower than 5% of turbine rated power, an abatement effectiveness up to 95% is achievable, but the cost may be as high as 25 k€ per year. Otherwise, in case of a maximum permitted fluctuation lower than 10%, abatement effectiveness over 92% is hardly achieved (the cost is over 30 k€ per year). For abatements around 90%, an annual cost between 15 and 20 k€ may be found using batteries rather than flywheels.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312747-ga1.jpg" width="354" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Ning Zhao, Fengqi You〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This article addresses the optimal design of waste-to-energy incentive policy for the dairy sector that aims to promote dairy farms’ adoption of on-farm anaerobic digesters and combined heat and power units to generate biomass-based energy. A modeling framework based on the single-leader-multiple-follower Stackelberg game is developed, where the government is the leader and the dairy farms are independent followers. The leader has two conflicting objectives, minimizing total government intervention, including total negative and positive cash flows of the government, and minimizing its unit cost on generating a target amount of bioelectricity. The government determines a bioenergy incentive policy consisting of subsidy on bioelectricity generation, refund of capital investment and dairy manure disposal fee, under a bioelectricity generation target. The dairy farms should react to the policy and maximize their net present values independently by making decisions on anaerobic digestion adoption and biogas-to-energy conversion technology selection. The problem is formulated as a multi-objective mixed-integer bilevel fractional program, and it is solved efficiently using a tailored global optimization algorithm which integrates a parametric algorithm and a projection-based reformulation and decomposition algorithm. A case study on hundreds of the largest dairy farms in New York State is presented to demonstrate the applicability of the proposed modeling framework and solution algorithm. Computational results show that incentive policies can effectively promote bioelectricity generation, and the refund of capital investment to a farm is 499% to 768% higher compared to the subsidy on bioelectricity generation. Additionally, the minimum government intervention to double the anaerobic-digestion-based bioelectricity generation is $11.8 million.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Jichao Hong, Zhenpo Wang, Wen Chen, Yongtao Yao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Voltage, temperature, and state of charge (SOC) are the main characterizing parameters for various battery faults that can cause these parameters’ abnormal fluctuations. Accurate prediction for these parameters is critical for the safe, durable, and reliable operation of battery systems in electric vehicles. This paper investigates a new deep-learning-enabled method to perform accurate synchronous multi-parameter prediction for battery systems using a long short-term memory (LSTM) recurrent neural network. A year-long dataset of an electric taxi was retrieved at the Service and Management Center for electric vehicles (SMC-EV) in Beijing to train the LSTM model and verify the model’s validity and stability. By taking into account the impacts of weather and driver’s behaviors on a battery system’s performance to improve the prediction accuracy, a Weather-Vehicle-Driver analysis method is proposed, and a developed pre-dropout technique is introduced to prevent LSTM from overfitting. Besides, the many-to-many(m-n) model structure using a developed dual-model-cooperation prediction strategy is applied for offline training the LSTM model after all hyperparameters pre-optimized. Additionally, the stability and robustness of this method have been verified through 10-fold cross-validation and comparative analysis of multiple sets of hyperparameters. The results show that the proposed model has powerful and precise online prediction ability for the three target parameters. This paper also provides feasibility for synchronous multiple fault prognosis based on accurate parameter prediction of the battery system. This is the first of its kind to apply LSTM to the synchronous multi-parameter prediction of the battery system.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Mohammad S. Roni, David N. Thompson, Damon S. Hartley〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Conventional practices of siting all biomass preprocessing operations at the biorefinery is widely believed to be the most cost-effective solution for feedstock supply because of economies of scale. However, biomass preprocessing operations could be decentralized by moving the preprocessing operations to distributed biomass preprocessing centers, also known as “depots” located near biomass sources. This study presents a comparative case study with multiple biomass resources to analyze biorefinery feedstock supply logistics designs having distributed depots and a primary depot co-located with the biorefinery. A mixed-integer linear programming model was developed to simultaneously optimize feedstock sourcing decisions, and optimal preprocessing depot locations and size, utilizing biomass resources from agricultural residue, energy and municipal solid waste to meet carbohydrate specifications and feedstock demand for a biochemical conversion process. Results from a case study in the US showed that a biorefinery could increase its feedstock supply draw area and supply volume by 57.3%, 177.4% respectively without increasing the feedstock delivered cost by adopting distributed depot-in the feedstock supply chain design. A distributed-depot-based supply chain can be more economical by selecting optimal mix of biomass resource, optimal siting and depot scales during feedstock supply chain design. The findings from this study indicate that a biorefinery can utilize dynamic blending to meet the feedstock quality specifications as well as larger supply radius in the distributed depot-based supply chain design to access more available biomass to handle potential feedstock supply uncertainty.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Ashwin Vinod, Arindam Banerjee〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Tidal turbines are deployed in sites which have elevated levels of free stream turbulence (FST). Accounting for elevated FST on their operation become vital from a design standpoint. Detailed experimental measurements of the dynamic near-wake of a tidal turbine model in elevated FST environments is presented; an active grid turbulence generator developed by our group was used to seed in the elevated FST and evaluate the influence of turbulence intensity (〈em〉T〈/em〉〈sub〉i〈/sub〉) and inflow integral length scale (〈em〉L〈/em〉) on the near-wake of the turbine. Three inflow conditions are tested: a quasi-laminar flow with 〈em〉Ti〈/em〉 ~ 2.2% and two elevated 〈em〉Ti〈/em〉 (~12–14%) cases, one with 〈em〉L〈/em〉 ~ 0.4〈em〉D〈/em〉 (〈em〉D〈/em〉 is the turbine diameter) and the other where 〈em〉L〈/em〉 ~ 〈em〉D〈/em〉. Elevated 〈em〉Ti〈/em〉 cases were found to increase the standard deviation of rotor torque by 4.5 times the value in quasi-laminar flow. Energy recovery was also found to be accelerated; at 〈em〉X〈/em〉/〈em〉D〈/em〉 = 4, the percentage of inflow energy recovered was 37% and was twice the corresponding value in quasi-laminar flow. Elevated FST was observed to disrupt the rotational character of the wake; the drop in swirl number ranged between 12% at 〈em〉X〈/em〉/〈em〉D〈/em〉 = 0.5 and 71% at 〈em〉X〈/em〉/〈em〉D〈/em〉 = 4. Elevated 〈em〉Ti〈/em〉 also resulted in 〈em〉L〈/em〉 that were considerably larger (〉2 times) than the quasi-laminar flow case. An increase in inflow integral length scale (from 0.4〈em〉D〈/em〉 to 〈em〉D〈/em〉) was observed to result in enhanced wake 〈em〉Ti〈/em〉, wake structures and anisotropy; however, no noticeable influence was found on the rate of wake recovery.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313261-ga1.jpg" width="266" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Victor Fransson, Hans Bagge, Dennis Johansson〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Low energy buildings are usually characterized by a very well insulated building envelope and an efficient ventilation system that makes use of the heat in the exhaust air. Internal heat gains from residents and their use of appliances can cover the heating demand to a certain extent. The magnitude of internal heat gains that cover demand are often modelled in a simplified way and thus can be associated with a large uncertainty. Hourly measurements of household electricity use in over 1000 apartments over a year, serves as a foundation for this study. These measurements show a large variation between households with regard to the annual electricity-use. Furthermore, each measurement series representing the unique behaviour in an apartment, shows a variation in household electricity use over time. Through Monte Carlo simulations that use the measurements as stochastic input, this study shows that heating energy demand can vary by up to 50% due to the different habits of residents in a building. This study also shows that the detail at which internal heat gains are modelled is not negligible regarding relative impact on energy and power demands for low-energy buildings. Reducing the resolution of the measurements from hourly to monthly means neglects important variations in the data, which in turn underestimates the heating power-demand.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): R.D. Merckel, F.J.W.J. Labuschagne, M.D. Heydenrych〈/p〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Junqiu Li, Danni Sun, Xin Jin, Wentong Shi, Chao Sun〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Overcharging is one of the main reasons causing lithium-ion battery thermal abuse, probably leading to vehicle accidents. This paper develops an impedance-based method to characterize the battery heat generation during overcharging process. An electro-thermal model is adopted for better computation efficiency. A series of overcharging experiments at 30 ℃ and 60 ℃ are conducted. Interestingly, three stages can be identified from the results, which are the normal heat-accumulating stage, fast heat-accumulating stage and thermal runaway stage, respectively (Stage I, II and III). During Stage I and II, pulse-relaxation and impedance-measurement methods are developed to parameterize the electro-thermal model, under different state of charge, temperature and charging rate conditions. Results of genetic algorithm with Hybrid Pulse Power Characteristic cycling data are used as benchmark. The simulated surface temperature results during overcharging are validated via experiments, which shows that medium frequency impedance method outputs better equivalent resistance and surface temperature estimation accuracy. The proposed model achieves to reduce the temperature estimation root mean squared error to under 0.9 ℃ in all overcharging situations, with greatly reduced computation complexity.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Qingli Tang, Wenchao Ji, Christopher K. Russell, Zhiwen Cheng, Yulong Zhang, Maohong Fan, Zhemin Shen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although experimental studies have shown that Ga〈sub〉3〈/sub〉Ni〈sub〉5〈/sub〉 is a promising catalyst for carbon dioxide (CO〈sub〉2〈/sub〉) hydrogenation to methanol (CH〈sub〉3〈/sub〉OH), the roles that cluster size and support play in the reaction are not clear. This research was set to study the quantitative and qualitative impacts of the size and support of Ga-Ni clusters on CO〈sub〉2〈/sub〉 hydrogenation to CH〈sub〉3〈/sub〉OH at electronic and molecular levels by using density functional theory (DFT). Ga〈sub〉3〈/sub〉Ni〈sub〉5〈/sub〉, Ga〈sub〉6〈/sub〉Ni〈sub〉10〈/sub〉, Ga〈sub〉12〈/sub〉Ni〈sub〉20〈/sub〉, Ga〈sub〉15〈/sub〉Ni〈sub〉25〈/sub〉, and Ga〈sub〉24〈/sub〉Ni〈sub〉40〈/sub〉 nanoclusters, and γ-Al〈sub〉2〈/sub〉O〈sub〉3〈/sub〉- and SiO〈sub〉2〈/sub〉- supported Ga〈sub〉6〈/sub〉Ni〈sub〉10〈/sub〉 were chosen as the study objects. Results show that adsorption energies of intermediates are highly related to intermediates’ characteristics and clusters’ active sites. Moreover, cluster size has no linear relation with the adsorption strengths of intermediates, while it has significant impact on the activation barrier of the rate-limiting step of hydrogenation process. Ga〈sub〉6〈/sub〉Ni〈sub〉10〈/sub〉 cluster has the lowest activation barrier of 1.04 eV due to the d-band center location and the exposed active sites of clusters. Compared with unsupported Ga〈sub〉6〈/sub〉Ni〈sub〉10〈/sub〉 clusters, Ga〈sub〉6〈/sub〉Ni〈sub〉10〈/sub〉/SiO〈sub〉2〈/sub〉 and Ga〈sub〉6〈/sub〉Ni〈sub〉10〈/sub〉/〈em〉γ-〈/em〉Al〈sub〉2〈/sub〉O〈sub〉3〈/sub〉 increase the adsorption energies of the intermediates and the activation barriers of the rate-limiting steps due to the lower electron transfer ability of Ga〈sub〉6〈/sub〉Ni〈sub〉10〈/sub〉 on SiO〈sub〉2〈/sub〉 and 〈em〉γ-〈/em〉Al〈sub〉2〈/sub〉O〈sub〉3〈/sub〉 supports. Therefore, a support that can increase the electron transfer abilities of catalysts are preferable. The findings will be very beneficial for preparing new Ga-Ni catalysts for CO〈sub〉2〈/sub〉 hydrogenation to CH〈sub〉3〈/sub〉OH.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312978-ga1.jpg" width="400" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Haowei Li, Hongwei Ma, Weijie Zhao, Xuehui Li, Jinxing Long〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Biofuel production from renewable resources is becoming an increasingly attractive option given the depletion of fossil fuels and the environmental problems caused by the excessive use of unsustainable energy resources. In this study, an efficient approach is provided for high-quality oxygen-containing fuel production from renewable lignin bio-oil. The results demonstrate that the calcination temperature has a remarkable effect on the catalyst structure, surface Ni content and physico-chemical properties of the Ni/MgO material, all of which result in significantly different performances in the upgrading of lignin bio-oil. At 160 °C for 4 h and 3 MPa of hydrogen, a 98% lignin bio-oil model compound of guaiacol is converted with 97% cyclohexanol selectivity in the presence of 15% Ni/MgO-850. Furthermore, the optimized catalytic system is reusable and shows good catalytic performance in the upgrading of both light and heavy lignin bio-oils, indicating that it is a promising strategy for renewable lignocellulosic biomass valorization.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312875-ga1.jpg" width="500" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Priybrat Sharma, Atul Dhar〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The automotive pollution norms throughout the world are getting increasingly stringent, which has made achieving the emissions regulation significantly challenging for the automakers. Additionally, energy security remains a matter of concern for all the economies due to depleting fossil fuels and fluctuating crude oil prices. These factors have motivated researchers to invest resources in the exploration of alternative fuels. Hydrogen has been consistently pitched and researched upon as a viable fuel for the future, meeting all these requirements. In this context, the presented work explores the dual fuel mode combustion in a single-cylinder constant speed engine. Under variation of engine load (25, 50 and 75%) different levels of hydrogen energy substitution are investigated. This study examines the combustion performance of hydrogen diesel dual-fuel through peak pressure location, cycle to cycle variability and combustion noise. The detrimental effects of hydrogen substitution at lower and mid loads are observed on the stability of combustion as cycle to cycle variability of combustion metrics show an increase. Additionally, the effect of hydrogen energy substitution on unregulated emissions like aldehydes and aromatics is reported. These unregulated emissions at these operating conditions are relatively unexplored despite being reported as carcinogens and precursors for soot formation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Vishwamitra Oree, Sayed Z. Sayed Hassen, Peter J. Fleming〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The growing importance of operational flexibility in generation expansion planning with increased integration of variable renewables has been regularly highlighted in recent research. Yet, operational flexibility has been largely overlooked in order to reduce the prohibitive problem size that results when operational details at small timescales are included in this long-term exercise. In this work, we present a multi-objective optimization framework that effectively and tractably incorporates flexibility screening of candidate generation portfolios in long-term generation expansion planning. Operational flexibility is considered as a separate objective along with the traditional economic and environmental objectives. The ability of the proposed methodology to provide valuable insights into the correlations between flexibility, total costs and carbon emissions is demonstrated using a case study. The results clearly reveal that omission of flexibility from the framework gives rise to deficient generation mixes that are unable to match the more frequent and steeper variations in net load. A high-level evaluation of the flexibility needed in generation portfolios to balance net loads with different degrees of variability is also provided. Finally, a procedure is proposed to support the decision-making process for selecting the most appropriate investment plan among the many solution options provided by the multi-objective optimization framework.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312632-ga1.jpg" width="254" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Amir Anees, Tharam Dillon, Yi-Ping Phoebe Chen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Due to the relatively high transportation cost of energy in remote regions, an effective and efficient energy trading market is required. In this paper, first, we extend the idea of a smart home community architecture comprising a small number of smart homes that suit these sorts of regions. Second, we propose an energy trading market at two levels. At the top-level, global generators and global consumers participate in energy trading. At the second level, smart homes in a smart home community participate in the energy market as local generators and consumers. Third, we develop a bilateral energy trading scheme and a novel decision strategy for choosing a bilateral price for both seller and buyer. The developed strategy and energy trading schemes are more efficient than those proposed in traditional work as they require far fewer rounds for negotiations between buyers and sellers to arrive at a mutually appropriate bilateral price. Fourth, we present two distinct cases for bilateral energy trading; single seller single buyer and single seller multiple buyers and show that the latter case has more benefits for both the seller and the buyer. Lastly, we conduct a series of experiments to illustrate the effectiveness of the proposed work.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312450-ga1.jpg" width="316" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Lisheng Pan, Bing Li, Weixiu Shi, Xiaolin Wei〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Compared with the conventional Rankine cycle, the CO〈sub〉2〈/sub〉 transcritical power cycle gives a higher thermal efficiency because of its high average heat absorbing temperature and is suitable for driving a compact system. The self-condensing CO〈sub〉2〈/sub〉 transcritical power cycle can solve the problem that CO〈sub〉2〈/sub〉 is difficult to condense in a conventional CO〈sub〉2〈/sub〉 transcritical power cycle using conventional water cooling. Based on solar thermal energy, a theoretical analysis model was established to study the relationship between the cycle performance and the operating parameters. The results showed that the thermal efficiency increases with increasing the cooled pressure with a low final cooled temperature. By increasing the final cooled temperature, a peak appears on the thermal efficiency curve. The outlet temperature of the cooling water is affected by a shift of the pinch point position in the cooler. According to the variation of the outlet temperature of the cooling water and the proportion of the mass flow rate of CO〈sub〉2〈/sub〉 in the power sub-cycle and that in the whole cycle, it can be concluded that conditions with a very low cooled pressure are uncontrollable. In these conditions, the maximum thermal efficiency of the self-condensing CO〈sub〉2〈/sub〉 transcritical cycle is 0.3463, which is 0.0313 a little lower than that of the supercritical CO〈sub〉2〈/sub〉 Brayton cycle. However, the novel cycle simplifies the development of the pressurizing component and avoids the liquid hammer in the pressurizing process.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312826-ga1.jpg" width="341" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Qinliang Tan, Yihong Ding, Qi Ye, Shufan Mei, Yimei Zhang, Yongmei Wei〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To transmit renewable energy on-grid over a large-scale power transmission system, an optimal dispatch model for a multi-energy power generation system is essential. This paper proposed a multi-energy hybrid power dispatch model for an integrated wind-photovoltaic-thermal power system. We consider five different dispatch modes and a dynamic carbon emissions trading system. Design of the modes was based on dispatch objectives. Power dispatch was based on interactive planning of power units and carbon emissions trading. To compare the modes, a comprehensive benefit evaluation index for dispatching is established. The proposed model was applied to supporting power supply system of the Tianzhong ultra-high voltage direct-current transmission project in Xinjiang, China. The results confirmed that high-efficiency mode is an optimal dispatch mode for the power transmission system, and has the most significant benefits. The impact on the optimal mode of the renewable energy penetration rate and carbon emissions trading system, as the two main factors, were further investigated. It was found that high-efficiency mode could maximize existing renewable energy generation and reduce coal consumption and carbon emission used for power generation and has a positive effect on carbon reduction. However, initial quotas need to be controlled more strictly than prices.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919312723-ga1.jpg" width="437" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Shifeng Fu, Yaqing Jin, Yuan Zheng, Leonardo P. Chamorro〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Wind-tunnel experiments were performed to inspect the impact of a variety of pitch and roll oscillations of a model wind turbine on the instantaneous power output and wake. Particle image velocimetry and hotwire anemometry were used to characterize the flow in the wake; instantaneous power output was also obtained in each of the configurations. For comparison, measurements were also performed in a fixed wind turbine. Results show that the wake at the turbine symmetry plane is significantly altered by the imposed motions, where rolling induced the lowest momentum deficit. The mean power output of the turbine increased with moderate tower oscillations, namely 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si45.svg"〉〈mrow〉〈mi〉≲〈/mi〉〈mn〉10〈/mn〉〈mi〉°〈/mi〉〈/mrow〉〈/math〉, independent of the type of motion. We argue that this is due to, at least, two distinctive processes. Namely, a relative gain due to the cube of the relative incoming velocity impinging the rotor in the pitching, and a momentum replenish in the rolling motion The power fluctuations exhibited a peak on the spectral content of the spectrum 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si46.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi mathvariant="normal"〉Φ〈/mi〉〈/mrow〉〈mrow〉〈mi〉P〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 coincident with the frequencies of the pitching and rolling. They also revealed the effects of the oscillation within the low-frequency content of 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si47.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi mathvariant="normal"〉Φ〈/mi〉〈/mrow〉〈mrow〉〈mi〉P〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉, which was likely due to the oscillation-driven changes in the aerodynamics of the blades. In particular, the pitch reduced the energy of the power fluctuations within frequencies below that of the pitching frequency, with stronger effect at larger amplitude of oscillations, 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si48.svg"〉〈mrow〉〈mi〉θ〈/mi〉〈/mrow〉〈/math〉. However, the roll motions reduced the energy of the power fluctuations in a relatively narrow band, and notorious only with 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si49.svg"〉〈mrow〉〈mi〉θ〈/mi〉〈mspace width="0.25em"〉〈/mspace〉〈mi〉≳〈/mi〉〈mspace width="0.25em"〉〈/mspace〉〈mn〉10〈/mn〉〈mi〉°〈/mi〉〈/mrow〉〈/math〉.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Antonio García, Javier Monsalve-Serrano, David Villalta, Rafael Lago Sari, Victor Gordillo Zavaleta, Patrick Gaillard〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The dual-mode dual-fuel combustion strategy allows operating over the entire engine map by implementing a diffusive dual-fuel combustion at high engine loads. This requires increasing the amount of exhaust gas recirculation to control the NOx emissions, which penalizes the soot levels. At these conditions, the use of non-sooting fuels as the e-Fischer Tropsch Diesel (e-FT) and oxymethylene dimethyl ethers (OMEx) could be a potential way to avoid the NOx-soot trade-off. The experimental results acquired in a compression ignition multi-cylinder medium-duty engine evidence that the higher oxygen content of OMEx allows reducing the soot emissions at high loads to near zero levels, while e-FT promotes a soot reduction of around 20% as compared to diesel. Nonetheless, the low lower heating value of OMEx leads to excessive injection durations, enlarging the combustion process and increasing the fuel consumption around 1.3–7.2% and 1.4–5.3% as compared to diesel and e-FT, respectively, depending on the engine load. Finally, the well to wheel analysis confirms the potential in reducing the carbon dioxide footprint of OMEx (14.8–69%) and e-FT (0.3–38.5%) compared to diesel, as they can be synthetized via direct air capture as a source of carbon and using renewable energy.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Jae Yong Cho, Jihoon Kim, Kyung-Bum Kim, Chul Hee Ryu, Wonseop Hwang, Tae Hee Lee, Tae Hyun Sung〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Unlike previous piezoelectric energy harvesters that generate electrical energy from a magnetic field according to the magnetic strength or magnetostrictive material, the proposed method achieves significant power enhancement using directional optimization of magnetization. This method can serve as a ubiquitous autonomous energy source that converts a magnetic field into usable electrical energy in a wireless sensor network for an (Industrial) Internet of Things (IIoT). The key approach in the proposed model is to increase of the Lorentz force by vertically adjusting the magnetic flux direction of a power cable and the magnetic direction of a tip magnet. In the simulation, a 3592 times higher y-axis Lorentz force was obtained in the vertical pole array, which resulted in about a 1.6 times higher output voltage. Then, we experimentally compared the electrical output performance of six different types of pole array according to the size and direction of the tip magnet. In a one-tip magnet (10 × 10 × 10 mm〈sup〉3〈/sup〉), the output power values were 2.34 mW (Vertical) and 1.23 mW (Horizontal) at 8 kΩ matching impedance. For two-tip magnets (20 × 10 × 10 mm〈sup〉3〈/sup〉), the output power values of the harvester were 39.2 mW (Planar-Vertical), 18.4 mW (Orthogonal-Vertical), 8.64 mW (Planar-Horizontal), and 0.05 mW (Orthogonal-Horizontal) at 5 kΩ matching impedance. It was found that the power generation differed by 2.13 to 784 times. With this method of power enhancement using multi-disciplinary research, we successfully constructed autonomous IoT and IIoT sensor systems for smart homes, smart buildings and smart factories.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): M. Krzaczek, J. Florczuk, J. Tejchman〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Effective and environmentally responsive techniques of energy management in residential buildings are desirable for the resulting reduction of energy costs and consumption. In this paper, an improved and efficient technique of energy management in pipe-embedded wall heating/cooling systems, called the Thermal Barrier, is described. Specifically, the Thermal Barrier is a technique focused on the management and control of heat supply into and heat extraction from external walls containing embedded pipes. The installed pipe-embedded wall heating/cooling system is fully controlled by a special fuzzy logic program that synchronizes the heat supply/extraction with variable heat loads. The main operation rule of the Thermal Barrier is to keep changes of the wall internal energy close to zero for the given reference temperature of a pseudo-surface created by an embedded pipe system of the wall heat exchanger. Comprehensive field measurement results associated with an example Thermal Barrier System installed in a residential two-story house are presented. These measurements confirmed the high-efficiency of the Thermal Barrier and its ability to use low-grade heat sources and sinks to effectively control an indoor climate. The supply water temperature was very low (25.3 °C) in the winter and very high (20.5 °C) in the summer. Daily variations of the indoor air temperature did not exceed 0.8 °C throughout the year. During the summer, the Thermal Barrier System operated in cooling-mode only from a low-grade renewable heat sink. The flexibility of the Thermal Barrier also allows for using heat sources/sinks different from those in the test house.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Vinícius Rückert Roso, Nathália Duarte Souza Alvarenga Santos, Ramon Molina Valle, Carlos Eduardo Castilla Alvarez, Javier Monsalve-Serrano, Antonio García〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The aim of this paper is to evaluate the potential of a prechamber ignition system to reduce the exhaust emissions and fuel consumption of commercial vehicles in the conditions proposed by the standardized and real-world driving cycles. For this purpose, a multi-cylinder engine was mapped in stationary conditions using two different combustion modes. First, the engine was tested under the baseline stoichiometric combustion with a spark plug ignition system. Second, the engine map was obtained using a stratified prechamber ignition system under lean conditions. Later, the experimental data was used as input for a computer model that simulates the vehicle operation with both concepts under different driving cycles. To run the model under real-world driving conditions, experimental data was acquired in a specific region in southern Brazil in conditions of heavy and free flow. Moreover, the conditions of the study were extended including two homologation cycles, the FTP-75 and WLTC. The results for the different cycles show similar average exhaust emissions and fuel consumption between WLTC and the real conditions of free flow traffic, and also between the FTP-75 and the real conditions of heavy flow traffic. The results also point out the potential of the prechamber ignition system to achieve a reduction of the engine-out CO and NO〈sub〉x〈/sub〉 emissions greater than 50% and 85%, respectively, as compared to the baseline stoichiometric combustion with a spark plug ignition, without penalizing the fuel consumption.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Yi Huang, Qun Yi, Jing-Xian Kang, Ya-Gang Zhang, Wen-Ying Li, Jie Feng, Ke-Chang Xie〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The coal chemical industry plays a critical role in the economic growth and energy security of China. In this study, a constrained nonlinear programming is proposed to optimize deployment technologies and processes of the coal chemical industry to reduce CO〈sub〉2〈/sub〉 emissions, and thus obtain the minimum CO〈sub〉2〈/sub〉 emissions per unit output of the coal chemical sector, while satisfying economic growth and energy security. Deployment of new technologies and processes in the coal chemical industry, over short-term (2020), mid-term (2030) and long-term (2050) periods, with the objective to reduce CO〈sub〉2〈/sub〉 emissions, are investigated based on this model. Dynamic sensitivity or uncertainty analysis of impacts of technical factors such as technology upgrading, carbon capture and storage & carbon capture, utilization, and storage and other technologies to deployed coal chemical sectors on CO〈sub〉2〈/sub〉 emissions reduction and economic growth, are performed. Different technologies were simulated, with the output providing three scenarios: 100% (positive), 50% (moderate) and 25% (conservative) of the predicted target reduction in CO〈sub〉2〈/sub〉 emissions. The reduction in CO〈sub〉2〈/sub〉 emissions was analyzed at different time periods, with respect to carbon tax values and crude oil prices. Correspondingly, a development roadmap (2020–2030–2050) of the coal chemical industry, with respect to reducing carbon emissions is drawn.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313716-ga1.jpg" width="383" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Ting Tan, Zhimiao Yan, Hongxiang Zou, Kejing Ma, Fengrui Liu, Linchuan Zhao, Zhike Peng, Wenming Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Natural and human environments are abundant of unused renewable energy such as mechanical energy, acoustic energy, electromagnetic energy, thermal energy, etc. The idea of designing multi-scale metamaterials with super-normal functions on energy manipulation is utilized in multi-field renewable energy harvesting and absorbing. The metamaterials are able to enhance the local energy density by confining and focusing the energy before it to be harvested, leading to remarkable improvement of the output power and conversion efficiency. Leveraging the multi-scale metamaterials for renewable energy harvesting is an emerging direction to exploit the excess energy in the natural and man-made environments. This paper provides a brief overview of the studies published over the past decade on mechanical, acoustic, electromagnetic and thermal energy harvesting using the relevant metamaterials. The goal is to spark the interest of new investigators to this unconventional but fast-evolving branch of energy harvesting that will impact the Internet of things, smart cities and sustainable developments.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Lukas Böhler, Gregor Görtler, Jürgen Krail, Martin Kozek〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Tighter legal emission limits require means to prevent releasing harmful substances into the atmosphere during the combustion of biomass. Economic considerations suggest to meet these restrictions by improving the ability to predict and therefore prevent emissions, which can be done by improved control algorithms. This work presents different methods to obtain models for the prediction of carbon monoxide emissions in a small-scale biomass combustion furnace for wooden pellets. The presented models are intended for an application in model based control, either as part of the underlying model or for carbon monoxide soft sensing and fault detection. The main focus is on simple structures which can be handled by the already existing hardware of the furnaces. Different black-box models and a kinetic process model are introduced and compared. The black-box models are based on the measured flue gas oxygen concentration and the combustion temperature, since these measurements are typically available even for smaller plants. The obtained models are validated with measured data in order to find the most suitable structures, of which combined fuzzy black-box models show the most promising results. The presented methodology can be readily applied to the investigated furnace. However, the model parameters have to be adapted for other plants.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313558-ga1.jpg" width="379" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Xiaoxia Yang, Sicong Tian, Tao Kan, Yuxiang Zhu, Honghui Xu, Vladimir Strezov, Peter Nelson, Yijiao Jiang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Efficient transformation of sewage sludge into bioenergy is currently a promising option to combat the energy crisis and mitigate climate change. Most attention has been paid to thermochemical H〈sub〉2〈/sub〉 production, however, effective approaches to utilize the carbon in sludge are lacking. Here we propose a novel two-stage sorption-enhanced thermochemical conversion process, which relies on the integration of a CaO-based CO〈sub〉2〈/sub〉 carrying cycle, to intensify the utilization of sludge carbon. In the process, the CO〈sub〉2〈/sub〉 generated during sludge pyrolysis at the first stage is captured and stored in the form of CaCO〈sub〉3〈/sub〉, and is then released at higher temperatures (the second stage) to gasify the sludge char for CO production. Under the conditions investigated in this study, the proposed process could produce 284.7 NmL of syngas per gram of dry sludge with a gross CO/H〈sub〉2〈/sub〉 molar ratio of 2.3, via obtaining a H〈sub〉2〈/sub〉-rich gas stream at 550 °C and a CO-rich gas stream at 750 °C, respectively. We conclude that the proposed process offers an efficient option for the production of syngas from sewage sludge with significantly intensified carbon utilization.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313509-ga1.jpg" width="500" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Rishav Chand, Venu Babu Borugadda, Michael Qiu, Ajay K. Dalai〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the present study, three different solvents – ethyl acetate, tetrahydrofuran and petroleum ether – were used to extract bio-crude from a hydrothermal liquefaction product mixture obtained from canola meal and waste wheat flour. The bio-crude yields and the ease of extraction were compared for each of the solvents to evaluate the efficacy of the solvent-extraction process and to determine the most suitable solvent for the same. Among the three solvents, ethyl acetate was identified as the most favourable option for solvent-extraction. The extraction carried out using ethyl acetate yielded significantly large amounts (bio-crude yield: 31.8 wt%) of an easy-to-handle, high quality bio-crude that is most suitable for further upgrading processes and eventual bio-diesel applications. The bio-crude extracted using ethyl acetate had a higher heating value of 46.0 MJ/kg, an oxygen content of 9.2 wt% and an ash content of 0.1 wt%. The aforementioned bio-crude exhibited the highest oxidation stability at room temperature with an induction period of 86.5 days and had a significant percentage of its compounds in the C〈sub〉13〈/sub〉-C〈sub〉24〈/sub〉 carbon range. The amounts of nitrogen and sulphur were quite low in all the bio-crude samples. Silica polymorphs such as quartz and α-cristobalite, along with calcium mica, were the dominant phases in all the bio-residue samples. The bio-residue obtained using ethyl acetate had the highest specific surface area (249 m〈sup〉2〈/sup〉/g) among the three bio-residue samples with an average pore volume of 0.37 cm〈sup〉3〈/sup〉/g and an average pore size of 7 nm.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Cynthia Kusin Okoro-Shekwaga, Andrew Barry Ross, Miller Alonso Camargo-Valero〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Anaerobic digestion of food waste is usually impacted by high levels of VFAs, resulting in low pH and inhibited methane production from acetate (acetoclastic methanogenesis); however, this could be harnessed for improving methane production via hydrogenotrophic methanogenesis (biomethanation). In this study, batch anaerobic digestion of food waste was conducted to enhance biomethanation by supplying hydrogen gas (H〈sub〉2〈/sub〉), using a gas mixture of 5%-H〈sub〉2〈/sub〉 and 95%-N〈sub〉2〈/sub〉. The addition of H〈sub〉2〈/sub〉 influenced a temporal microbial shift in substrate utilisation from dissolved organic nutrients to H〈sub〉2〈/sub〉 and CO〈sub〉2〈/sub〉 and was perceived to have enhanced the hydrogenotrophic methanogenic activity. As a result, with the release of hydrogen as degradation progressed (secondary fermentation) hydrogenotrophic methanogenesis was further enriched. This resulted in an enhancement of the upgrading of the biogas, with a 12.1% increase in biomethane (from 417.6 to 468.3 NmL-CH〈sub〉4〈/sub〉/gVS〈sub〉added〈/sub〉) and 38.9% reduction in CO〈sub〉2〈/sub〉 (from 227.1 to 138.7 NmL-CO〈sub〉2〈/sub〉/gVS〈sub〉added〈/sub〉). Furthermore, the availability of hydrogen gas at the start of the process promoted faster propionate degradation, by the enhanced activity of the H〈sub〉2〈/sub〉-utilisers, thereby, reducing likely propionate-induced inhibitions. The high level of acidification from VFAs production helped to prevent excessive pH increases from the enhanced hydrogenotrophic methanogenic activity. Therefore, it was found that the addition of hydrogen gas to AD reactors treating food waste showed great potential for enhanced methane yield and biogas upgrade, supported by VFAs-induced pH buffer. This creates the possibility to optimise hydrogenotrophic methanogenesis towards obtaining biogas of the right quality for injection into the gas grid.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Matteo Policella, Zhiwei Wang, Kiran. G. Burra, Ashwani K. Gupta〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The growing problem of waste tire generation worldwide can be converted from a major environmental issue to a valuable energy source using the thermochemical conversion processes. CO〈sub〉2〈/sub〉 gasification can offer a prominent position in the tire waste to energy panorama since it offers high quality syngas production and direct mitigation pathway for greenhouse gas emissions. An evaluative study of syngas yield and quality between pyrolysis and CO〈sub〉2〈/sub〉 assisted gasification has been carried out in a laboratory scale fixed bed reactor in this work. Pyrolysis was performed in the temperature range of 673–1173 K and gasification at temperatures of 973–1273 K in steps of 100 K. Flow rates of syngas and its major gaseous components (CO, H〈sub〉2〈/sub〉, CH〈sub〉4〈/sub〉) for both the processes and on CO〈sub〉2〈/sub〉 consumption during gasification were reported. The results provided direct comparison between pyrolysis and gasification and also on cold gas efficiency. Results showed that gasification temperature strongly affects the syngas yield, quality, and energy content. Gasification reactions below 973 K were negligible. Char reactivity even at higher temperature was found to be low. Gasification resulted in 3.3 times increase in CO yield at 1073 K and 2.8 times increase at 1173 K as compared to pyrolysis. The increase in gasification temperature from 1173 to 1273 K enhanced CO yield by 1.5 times. While pyrolysis provided higher efficiency from a merely energetic point of view, gasification still presented high cold gas efficiency of 62.6% at 1273 K and an overall efficiency greater than 30%. In addition, CO〈sub〉2〈/sub〉 assisted gasification of waste tire provided a direct pathway to utilize green-house gas that showed carbon dioxide consumption of 0.75 g/gram of scrap tire gasified at 1273 K, and produced significant amounts of valuable CO, which offers good value for both energy production and fuel, and to value-added products with further synthesis.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Jesus Lizana, Manuel de-Borja-Torrejon, Angela Barrios-Padura, Thomas Auer, Ricardo Chacartegui〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Global warming is gradually increasing the cooling energy demand of buildings. Phase change materials (PCM) offer high potential to passively reduce cooling energy consumption and overheating by absorbing heat gains in the daytime through their melting process, and releasing the heat at night while solidifying by taking advantage of free cooling through natural ventilation. However, the effectiveness of PCM-based solutions highly depends on the implementation techniques, material properties, environmental conditions and occupants’ behaviour. This paper analyses the performance of PCM-based solutions towards passive and low-energy cooling through a parametric study carried out in TRNSYS, in order to identify main design criteria for their optimal implementation. Two PCM implementation alternatives are assessed: a conventional passive application based on a PCM layer attached at the ceiling in contact with the indoor space, in which the heat transfer between PCM and air is based on natural convection; and an optimised low-energy application designed as a PCM layer integrated inside the suspended ceiling, in which the air flow is forced by a fan to enhance the heat transfer between PCM and the air. Both solutions are studied with and without the simultaneous operation of air-conditioning systems. A dwelling in a multi-family building was selected as a reference scenario. The results show that in the scenario with no participation of air-conditioning systems, the optimised PCM-based solution could reduce discomfort hours by 65% regarding the adaptive comfort model, and up to 83% through additional improvements in order to increase the heat transfer between PCM and air. On the other hand, the simulations reflect that both PCM-based solutions do not provide benefits in scenarios with an intermittent operation of air-conditioning systems. This study concludes with design criteria and strategies for an optimal implementation of PCM towards low-carbon buildings.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Sihui Li, Guangcai Gong, Jinqing Peng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The existing selection methods for air-source heat pumps often result in insufficient heating effects and high electricity consumption in winter, in China's hot-summer/cold-winter zone. Because the existing basis for selection are diverse and difficult to convert for comparison, selection methods are not connected with actual dynamic load demand. This paper presents a dynamic coupling selection method for air-source heat pumps based on load balance. Dynamic output capacity models and energy efficiency models for air source heat pumps, dynamic load demand models for buildings, and dynamic coupling models are established to interpret the relationships between heat pumps and buildings. This paper puts forward the stable operation conditions, the output capacity, and the energy efficiency of heat pumps under the most unfavorable operation conditions, in order to select units. Our study finds that the lowest coefficient of performance is 1.12, which is only 43% of the rated value in the region. Heat pumps with higher performance generated excessive cooling capacity relative to load demands of buildings. Hence, the dynamic coupling method is a simple and engineering tool for optimizing entire air-source heat pump energy systems in buildings by matching the performance surfaces of heat pumps and buildings. It is a general method which can be applied by users to directly compare different units in buildings with higher energy efficiency and operation reliability, and also to guide manufacturers with a performance surface to complement existing indexes. This method has great significance for selection optimization and promotion of air-source heat pumps.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Measrainsey Meng, Kelly T. Sanders〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The efficiency of a thermoelectric generator is dependent on a number of operational and climatic variables, including ambient air temperature. To date, there has not been a data-driven analysis of the impacts of climate variability on electricity generator performance that includes a statistically representative set of generators. This study develops regression models to estimate changes in the efficiencies of over one thousand coal and natural gas generators as a function of ambient air temperature and operational variables, across different fuel types, prime movers, cooling systems, and climate zones during the years ranging from 2008 to 2017. The efficiencies of generators with dry cooling, particularly those in hot and dry climates, demonstrated the greatest sensitivity to increases in ambient temperature. Results for generators utilizing wet cooling systems were largely inconclusive, most likely because other factors, such as cooling water temperature, are better predictors of efficiency. Natural gas combustion generator efficiencies exhibit large sensitivities to rises in air temperature in theoretical models but had a counterintuitive trend in our findings, where losses were relatively small in the hottest and driest climates. This result is likely due to the fact that natural gas combustion generators in hot and arid regions often utilize inlet air cooling technologies to reduce the temperature of ambient air before it enters the compressor, thereby mitigating efficiency losses. The analytical framework developed offers generalized methods for cleaning, processing, and merging federally available electricity generation and climate datasets to increase their value in future studies.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Chao Xu, Dagmar Haase, Meirong Su, Zhifeng Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉It remains a matter of debate whether compact urban development can be a sustainable approach to mitigating greenhouse gas (GHG) emissions, although the compact city theory and GHG emissions have both gained increasing attention. The present study explored the relationship between urban compactness and energy-related per capita GHG emissions among different countries using panel data models. To obtain the energy-related GHG emissions, the GHGs emitted by the energy sector were calculated on a per capita basis according to the “2006 IPCC guidelines for national GHG inventories”. Urban compactness was assessed by two indicators, namely population density and the compactness index, of which the latter measures the overall physical compactness of urban land patches. The case study of the 28 EU member countries during 2000–2012 demonstrated that the two indicators did not correlate with each other and they affected energy-related per capita GHG emissions in contrasting ways. That is to say, population density and the overall physical compactness of urban land patches exerted significant negative and positive influences on energy-related per capita GHG emissions, respectively. These findings imply that high population density, mixed-use urban development with a lower degree of physical compactness is advisable in terms of reducing energy footprints and mitigating GHG emissions. However, consideration should also be given to maintaining a balance between effectively reducing GHG emissions and preventing disadvantages associated with high-density urban development in future urban planning practices.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Xiaofeng Ding, Donghuai Zhang, Jiawei Cheng, Binbin Wang, Patrick Chi Kwong Luk〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes an improved Thevenin model of the Lithium-ion battery taking into account temperature influence on the calculation accuracy of the open circuit voltage of a battery. The calculation accuracy of the terminal voltage of a battery is improved without increasing the order of the model. Firstly, the model was proposed based on Thevenin model and the relationship between the open-circuit voltage and the state of charge. Then, based on the experimental results of the open-circuit voltage test and hybrid power pulse characteristic test, the parameters of the battery model were identified by polynomial fitting and genetic algorithm, respectively. Furthermore, the temperature effects were considered in both the open-circuit voltage and hybrid power pulse characteristic tests. Finally, the proposed model was tested and verified by experiments under the Dynamic Stress Test condition and the Urban Dynamometer Driving Schedule at different temperatures. The accuracy of the proposed model is high and the parameter identification error is less than 1%.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Ling Min Tan, Hadi Arbabi, Paul E. Brockway, Danielle Densley Tingley, Martin Mayfield〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Cities have evolved as centers of economic growth and often described as open systems where the intake of resources is heavily dependent on flows imported from the external environment. The question is, how much of the resource available in cities is effectively utilized? In response, this paper develops an ecological-thermodynamic approach to assess the ability of a system to make full use of the resources available and reduce the demand for new resources. In this work, open system network effectiveness analysis is introduced as a novel assessment method to investigate the cities’ producer and consumer behaviors by studying the resource flow connections and the interactions between the socio-economic sectors. Investigation on the urban flows network evaluates the ability of the system to utilize the resource imported through the effectiveness of utilization indicator and the ability to convert the resource imported to useful products through the effectiveness of conversion indicator. The effectiveness indicators, utilization and conversion, represent the consumption and production characteristics of the system respectively. This is tested through a case study conducted for Singapore city over the time period 2005–2014. The effectiveness results show that the city, on average, has utilized 45% of the maximum extractable usefulness from the resources imported throughout the years, with the lowest effectiveness, 39%, and the highest effectiveness, 50%, in the years 2007 and 2014 respectively. The trajectory of effectiveness results throughout the years suggests a trade-off relationship between the producers and consumers to balance the production and consumption of resources in the city.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Hui Liu, Chao Chen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Accurate wind speed prediction is essential for proper use of wind energy resource. In this paper, a novel hybrid multi-step wind speed forecasting model is developed, which consists of sparse feature extraction, bidirectional deep learning, multi-objective optimization, and adaptive decomposition-based error correction. Apart from the traditional average-based resolution transformation method, a two-layer stacked sparse autoencoder (SSAE) is proposed to extract the hidden representation of original 3 s high-resolution wind speed data. Trained by the data generated from different resolution transformation methods, two bidirectional long short-term memory (BiLSTM) networks serve as base predictors and provide 10-step forecasting results. The results of base predictors are reasonably ensembled by multi-objective multi-universe optimization (MOMVO). Moreover, to reduce the predictable components in error series further, a correction model based on empirical wavelet transform (EWT) and outlier robust extreme learning machine model (ORELM) is constructed to reduce the forecasting error further. The effectiveness of the proposed hybrid model is comprehensively evaluated by a series of experiments. The experimental results demonstrate that: (a) the proposed model is well trained, with great convergence, and an average RMSE of 0.2618 m/s in 10-step forecasting; (b) the proposed model outperforms other existing models in all experimental sites and forecasting steps; (c) the multi-objective optimization algorithm can rationally integrate base predictors to obtain better performance in each step; (d) the proposed residual error correction model can generate more than 78% improvement of RMSE, significantly better than compared correction methods.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Jachin Gorre, Felix Ortloff, Charlotte van Leeuwen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The publication gives an overview of the production costs of synthetic methane in a Power-to-Gas process. The production costs depend in particularly on the electricity price and the full load hours of the plant sub-systems electrolysis and methanation. The full-load hours of electrolysis are given by the electricity supply concept. In order to increase the full-load hours of methanation, the size of the intermediate hydrogen storage tank and the size of the methanation are optimised on the basis of the availability of hydrogen. The calculation of the production costs for synthetic methane are done with economics for 2030 and 2050 and the expenditures are calculated for one year of operation. The sources of volume of purchased electricity are the short-term market, long-term contracts, direct-coupled renewable energy sources or seasonal use of surpluses. Gas sales are either traded on the short-term market or guaranteed by long-term contracts. The calculations show, that an intermediate storage tank for hydrogen, adjustment of the methanation size and operating electrolysis and methanation separately, increase the workload of the sub-system methanation. The gas production costs can be significantly reduced. With the future expected development of capital expenditures, operational expenditure, electricity prices, gas costs and efficiencies, an economic production of synthetic natural gas for the years 2030, especially for 2050, is feasible. The results show that Power-to-Gas is an option for long-term, large-scale seasonal storage of renewable energy. Especially the cases with high operating hours for the sub-system methanation and low electricity prices show gas production costs below the expected market prices for synthetic gas and biogas.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Nan Shang, Chengjin Ye, Yi Ding, Teng Tu, Baofeng Huo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The generation right trades (GRTs) are of great significance for the improvement of unit utilization hours and reduction of carbon emission, which plays an important role in the cross-regional electricity transactions. In order to hedge the risk in spot markets and ensure the incomes, it is crucial for generation companies (Gencos) to determine the optimal GRT scheme at their risk preferences. In this paper, a power portfolio optimization methodology is proposed considering the bidding behaviours in spot markets, independent system operator (ISO) centralized dispatching, and the cross-region GRTs. Specifically, various risks for Gencos are modelled including spot price fluctuation and system component failures. Then, a bi-level optimal portfolio (BLOP) model is established where the Gencos maximize their total incomes with subject to the ISOs which minimize the local dispatching costs simultaneously. The BLOP model is transformed into a solvable single-level mathematical program with equilibrium constraints (MPCE) through the Karush-Kuhn-Tucker (KKT) conditions. The numerical results on a realistic Chinese testing system illustrate the effect of GRTs for income assurance of Gencos and the necessity to consider the stochastic contingencies in portfolio decisions. Specifically, it is a preferred option for Gencos to exploit approximately 77% of spot power to GRT at the normal state, which can increase the total income by 266.21%. At contingency states, the optimal GRT ratios are 70–80%, the corresponding income grows nearly twice more than pure spot trades.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Narjes Abbasabadi, Mehdi Ashayeri, Rahman Azari, Brent Stephens, Mohammad Heidarinejad〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Many urban energy use modeling tools and methods have been developed to understand energy use in cities, but often have limitations in aggregating across multiple scales and end-uses, which adversely affects accuracy and utility. Increased data availability and developments in machine learning (ML) provide new possibilities for improving the accuracy and complexity of urban energy use models. This paper presents an integrated framework for urban energy use modeling (UEUM) that localizes energy performance data, considers urban socio-spatial context, and captures both urban building operational and transportation energy use through a bottom-up data-driven approach. The framework employs ML techniques for building operational energy use modeling at the urban scale with a travel demand model for transport energy use prediction. The framework is demonstrated using Chicago as a case study because it has significant variations in urban spatial patterns across its neighborhoods and it provides publicly available data that are essential for the framework. Results for Chicago suggest that, among the tested algorithms, k-nearest neighbor shows the best overall performance in terms of accuracy for a single-output model (i.e., for building or transportation energy use separately) and artificial neural network algorithm is the most accurate for the integrated model (i.e., building and transportation energy use combined). Exploratory analysis demonstrates that the urban attributes examined herein explain 41% and 96% of the variance in building and transportation energy use intensity, respectively. The UEUM framework has the potential to aid designers, planners, and policymakers in predicting urban energy use and evaluating robust theories and alternative scenarios for energy-driven planning and design.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Qinghua Lai, Lingli Kong, Weibo Gong, Armistead G Russell, Maohong Fan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The conventional regeneration processes for aqueous amine-based sorbents require high regeneration temperature and are very energy intensive. In this work, a low-temperature and energy-saving CO〈sub〉2〈/sub〉 capture technology has been successfully developed by using alcohols-amines-water mixtures as sorbents. The addition of certain amounts of alcohols [especially ethanol (EtOH)] to amines can significantly increase the CO〈sub〉2〈/sub〉 desorption rates and cyclic CO〈sub〉2〈/sub〉 capture capacities in comparison with those of monoethanolamine-water, diethanolamine-water, and methyldiethanolamine-water systems. The sorbent containing 40 wt% EtOH, 20 wt% monoethanolamine (MEA), and 20 wt% H〈sub〉2〈/sub〉O can increase cyclic CO〈sub〉2〈/sub〉 capture capacity by 6.8 times and a maximum improvement of 236 times in CO〈sub〉2〈/sub〉 desorption rate at 75 °C, which makes the use of the low-temperature waste heat in power plants for CO〈sub〉2〈/sub〉 capture or self-supported CO〈sub〉2〈/sub〉 capture in power plants possible. To the best of authors’ knowledge, this is the first time that Raman and Fourier transform infrared spectroscopy characterizations have been used to confirm that ethanol in EtOH-MEA-H〈sub〉2〈/sub〉O can change the reaction pathway by forming C〈sub〉2〈/sub〉H〈sub〉5〈/sub〉OCO〈sub〉2〈/sub〉〈sup〉−〈/sup〉 instead of HCO〈sub〉3〈/sub〉〈sup〉−〈/sup〉, which is difficult to decompose. In addition, the experimental results confirm that the new technology can significantly avoid amine degradation – a common challenge of the state-of-the-art CO〈sub〉2〈/sub〉 capture technologies. Therefore, the new CO〈sub〉2〈/sub〉 capture technology is promising from the perspectives of energy saving and environmental protection.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0306261919313832-ga1.jpg" width="295" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Qiang Cheng, Zeeshan Ahmad, Ossi Kaario, Larmi Martti〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Cyclic variations constitute an inherent consequence of the flow, thermal and concentration field variations between cycles. They are understood to lead to lower efficiency and higher emissions. The current investigation aims to evaluate the cycle-to-cycle variations (CCVs) based on 2D visualization and cylinder pressure in an optically accessible heavy-duty engine fueled with methane (main fuel) and diesel (pilot fuel). A high-speed color camera is employed to measure the combustion behavior based on natural luminosity (NL). Proper orthogonal decomposition (POD) is applied to reconstruct and analyze the images. The POD-based coefficient of variation (COV) is implemented to evaluate the cyclic variability, along with the pressure-based and global intensity-based COV. This coefficient is then adopted to discriminate the coherent and incoherent parts from the fluctuations in the luminosity field. The POD-based and global intensity-based COV presents the variations in the luminosity field, which can provide information on chemical kinetics, while pressure-based COV provides a general description of the cyclic fluctuation of thermodynamics. To extract more information from the NL images, the color-intensity COV analysis based on the intensity separated from RGB channels is adopted to estimate the CCVs from the aspect of spectral emissions (excited and ionized radicals in the flame). Finally, the effects of methane lambda, pilot fuel rate and charge air temperature on the CCVs were analyzed systematically. The results revealed that richer methane conditions has an inhibitive effect on the CCVs. The appearance of the CCVs were determined by the ignition characteristics of the pilot fuel. A critical point was found in charge air temperature, when the charge air temperature lower than the critical point, the increase of the charge air temperature has a promotive effect on the CCVs; after that, it has an inhibitive effect on the CCVs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 254〈/p〉 〈p〉Author(s): Guangya Zhu, T.T. Chow, K.F. Fong, C.K. Lee〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The urge for more energy-efficient power plant systems to relieve the energy crisis triggers the design for more advanced power cycles. The humidified gas turbine cycle is considered one of the potential choices, and the air saturator performance is critical to the energy merit of such kind of system. To understand more, the performances of humidified gas turbine cycles with two types of air saturator designs were compared in this study. Type 1 air saturator was a hybrid design which combined an indirect evaporative cooler with a Maisotsenko cycle while Type 2 was a conventional indirect evaporative cooler. Detailed heat and mass transfer analysis was taken into account in the air saturator modelling. Through system simulations, it was found that all the humidified gas turbine cycle systems offered higher system efficiencies than a simple gas turbine system with recuperator. Besides, parametric studies were conducted which highlighted the effects of system inlet air temperature, turbine inlet temperature, water injection rate, and part-load ratio on the performances of the different humidified gas turbine cycle designs. The employment of Type 1 air saturator offered 9.34% and 23.55% enhancement in the system efficiencies as compared to those using Type 2 air saturator under the design and 50% part-load ratio conditions respectively. This reinforced the benefit of applying Maisotsenko cycle to the air saturator design of humidified gas turbine cycle for the enhancement of system efficiency.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 253〈/p〉 〈p〉Author(s): Guijun Ma, Yong Zhang, Cheng Cheng, Beitong Zhou, Pengchao Hu, Ye Yuan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Accurate estimation of the remaining useful life of lithium-ion batteries is critically important for electronic devices. In the existing literature, the widely applied model-based approaches for remaining useful battery life estimation are limited by the complexity of the electrochemical modeling required. In addition, data-driven approaches for remaining useful battery life estimation commonly define unreliable sliding window sizes empirically and the prediction accuracy of these approaches needs to be improved. To address the above issues, use of a hybrid neural network with the false nearest neighbors method is proposed in this paper. First, the false nearest neighbors method is used to calculate the sliding window size required for prediction. Second, a hybrid neural network that combines the advantages of a convolutional neural network with those of long short-term memory is designed for model training and prediction. Remaining useful life prediction experiments for batteries with various rated capacities are performed to verify the effectiveness of the proposed approach, and the results demonstrate that the proposed approach offers wide generality and reduced errors when compared with the other state-of-the-art methods.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: 15 May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Applied Energy, Volume 242〈/p〉 〈p〉Author(s): Siyue Guo, Da Yan, Tianzhen Hong, Chan Xiao, Ying Cui〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The global climate change has resulted in not only warmer climate conditions but also more frequent extreme weather events, such as heat waves. However, the impact of heat waves on the indoor environment has been investigated in a limited manner. In this research, the indoor thermal environment is analyzed using a building performance simulation tool for a typical residential building in multiple cities in China, over a time period of 60 years using actual measured weather data, in order to gain a better understanding of the effect of heat wave events. The simulation results were used to analyze the indoor environment during hot summers. A new kind of weather data referred to as the typical hot year was defined and selected based on the simulated indoor environment during heat waves. The typical hot-year weather data can be used to simulate the indoor environment during extreme heat events and for the evaluation of effective technologies and strategies to mitigate against the impact of heat waves on the energy demand of buildings and human health. The limitations of the current study and future work are also discussed.〈/p〉〈/div〉 〈/div〉