ALBERT

Description: Among responses to governmental regulations for curbing carbon emissions, outsourcing carbon reduction to a specialized third-party is an important means to satisfy a variety of carbon-emission restraints. In this situation, however, designing efficient contracts for emission reducing while retaining appropriate supply-chain profit is a substantial but challenging problem. We therefore refine this from practice and consider a low-carbon supply chain consisting of one manufacturer and one retailer to analyze in which conditions the system should outsource its carbon reduction efforts to an external expert firm under the assumption that consumers with a sense of social responsibility prefer low carbon products. In the decarbonization expert firm embedded supply chain, we examine the respective impacts of three cost-pooling schemes for emission reduction on supply chain performances. We find that the manufacturer-undertaking contract is the worst in terms of profit and carbon reduction level among the contracts being studied, while the retailer-undertaking contract yields the best outcome in terms of the profit and performs well in carbon reduction when the contractor has cost efficiency in carbon reduction, which is even better than the joint-undertaking contract in carbon reduction when the contractor is inefficient. The study shows the diversity of contracts on outsourcing carbon reduction significantly impacts the supply chain profitability, carbon reduction efficiency and sustainability of operations.

Description: To solve the issues of frequent and inflexible contact charging system for inspection robots, the dynamic wireless charging system for the moving robot is introduced in this paper. In dynamic wireless charging systems with symmetric transceiver, including a single energized transmitting coil and one receiving coil, the receiving power drops significantly when the receiving coil moves to the boundary position of the energized transmitting coil. An asymmetric transceiver, including the single energized transmitting coil and two identical receiving coils connected in series is proposed for power stabilization during the moving process of the inspection robot. Circuit models of the systems with symmetric and asymmetric transceivers are developed. Expressions for the receiving power and the efficiency in these systems are derived. Then, the characteristics of the receiving power and efficiency varying with the position of receiving devices during one cycle of the switching control of the transmitting coils are investigated comparatively. The receiving power drop issue when the receiving coil is at the switching control position of the transmitting coils in the system with symmetric structure is solved by the proposed asymmetric structure with two receiving coils. Finally, the theoretical analyses are verified by experimental results and conclusions are drawn.

Description: The efficiency of an internal combustion engine (ICE) is essential for automobiles and motorcycles. Several studies have demonstrated that the homogeneous charge compression ignition (HCCI) is a promising technology for realizing engines with high efficiency and low emissions. This study investigated the combustion characteristics of the HCCI using a 125 cc motorcycle engine with n-heptane fuel. The engine performance, combustion characteristics, and thermal efficiency were analyzed from experimental data. The results revealed that a leaner air–fuel mixture led to higher engine efficiency and output. The improvement of engine output is contradictory to the general trend. Energy balance analysis revealed that lower heat loss, due to the low cylinder gas temperature of lean combustion, contributed to higher efficiency. A double-Wiebe function provided excellent simulation of the mass fraction burned (MFB) of the HCCI. Air cycle simulation with the MFB, provided by the double-Wiebe function, was executed to investigate this phenomenon. The results indicated that a better combustion pattern led to higher thermal efficiency, and thus the engine output and thermal efficiency do not require a fast combustion rate in an HCCI engine. A better combustion pattern can be achieved by adjusting air–fuel ratio (AFR) and the rates of dual fuel and exhaust gas recirculation (EGR).

Description: Research on concentrated solar power (CSP) plants has been increasing in recent years. Supercritical carbon dioxide (S-CO2) has been applied to solar power plants due to its promising physical properties. S-CO2 has a relatively low critical temperature of 31.1 °C and owns high density in the supercritical region. Hence, it is a vital working fluid in the application of low temperature heat source and miniature power equipment. Due to the fact that solar power system has a constantly changing heat source according to season and weather, a satisfactory off-design performance is necessary for the turbine in a solar power system. In this work, a S-CO2 radial-inflow turbine based on CSP is designed. A thorough numerical analysis of the turbine is then performed. To investigate the off-design performance of this turbine, three types of nozzle profiles with different leading edge diameters are adopted. Mach number, temperature and pressure distribution are covered to present the off-design effect with different nozzle profiles. Moreover, the relation of output power, mass flow rate and efficiency with different leading edge diameter (LED) are analyzed. Results show that different LED has a vital influence on the aerodynamic characteristics and off-design performance of the S-CO2 turbine based on CSP. In addition, the designed turbine with LED = 4 mm can obtain the highest mass flow rate and output power. While the turbine with LED = 10 mm provides slightly better off-design efficiency for CSP plants.

Description: The ever-increasing penetration of wind power generation and plug-in electric vehicles introduces stochastic continuous disturbances to the power system. This paper proposes an analytical approach to analyze the influence of stochastic continuous disturbances on power system small signal stability. The noise-to-state stability (NSS) and NSS Lyapunov function (NSS-LF) are adopted for stability analysis with respect to the magnitude of uncertainties in a power system. The power system is modeled as a set of stochastic differential equations (SDEs). The supremum of the norm of the covariance is employed to characterize the influence of magnitudes of uncertainties on the power system. Then the relationship between the magnitudes of stochastic variations and probabilistic stability is explicitly identified by NSS. The proposed method can assess the stochastic stability of the power system by checking some algebraic expressions. Hence, it has high computation efficiency compared with the well-established Monte Carlo based method. Besides, since the magnitudes of the stochastic variations are integrated into the definition of the stochastic stability, the proposed method provides theoretical explanations for the impacts of uncertainties.

Description: The background shows that intervention on historical walls highlights the difficulty of identifying design solutions that are effective and compatible due to the lack of specific data on the thermal characteristics of the specific contexts investigated. This determines the choice of design solutions that are frequently inadequate and unsustainable from an environmental and economic point of view. Starting from acquired data a methodology has been developed that is based on in situ experimental investigations able to return the most probable value of transmittance of the historical walls. The values measured on the samples analysed do not reflect the literature data. For some of the samples analysed, the measured transmittance is lower than the one recorded in literature of about 10–15%. For the remaining ones, there are no reference values. The importance of an in-depth knowledge of the real behaviour of an existing historical envelope of a building is therefore fundamental, given that any evaluation mistake can have serious consequences from both an economic and environmental point of view. Underestimating the transmittance of a wall implies a waste in the use of available resources but also the disposal of greater quantities of building materials in relation to the end of life. The developed methodology can be easily replicated in other contexts and extended to all building elements that make up the historical envelope. The study will be continued by analysing further samples in order to create a reference knowledge database accessible to researchers, professionals and organizations.

Description: Uncertainties associated with the loads and the output power of distributed generations create challenges in quantifying the integration limits of distributed generations in distribution networks, i.e., hosting capacity. To address this, we propose a distributionally robust optimization-based method to determine the hosting capacity considering the voltage rise, thermal capacity of the feeders and short circuit level constraints. In the proposed method, the uncertain variables are modeled as stochastic variables following ambiguous distributions defined based on the historical data. The distributionally robust optimization model guarantees that the probability of the constraint violation does not exceed a given risk level, which can control robustness of the solution. To solve the distributionally robust optimization model of the hosting capacity, we reformulated it as a joint chance constrained problem, which is solved using the sample average approximation technique. To demonstrate the efficacy of the proposed method, a modified IEEE 33-bus distribution system is used as the test-bed. Simulation results demonstrate how the sample size of historical data affects the hosting capacity. Furthermore, using the proposed method, the impact of electric vehicles aggregated demand and charging stations are investigated on the hosting capacity of different distributed generation technologies.

Description: The building sector is responsible for a large part of the overall energy demand in Europe. Energy consumption may be reduced at the design stage by selecting the proper building elements. This study develops a multi-objective analysis for a highly efficient slab-on-ground floor, whose design is optimized for a warm climate. Possible floor configurations have been obtained using the software tools modeFRONTIER, for the multi-objective analysis, and MATLAB, for the computational code. To proceed with the optimization of the different floor layers, a dataset has been developed for several materials in relation to a number of parameters: thermo-physical properties, eco-sustainability score according to the ITACA Protocol, costs, source, and structural features. Results highlight how a high surface mass is preferable when guaranteed by concrete in the innermost and outermost layers. Furthermore, insulating materials are better placed in the middle layers, with the insulating and synthetic materials adjacent to the ground and insulating and natural materials adjacent to the floor. Results emphasize the importance of thermal transmittance close to the Italian regulation limit (0.38 W/m2 K) in the climatic zone C, to allow an adequate exchange with the ground in summer, avoiding overheating. The outcomes show that the obtained slab-on-ground floor configurations favor the use of local, recyclable, sustainable, and eco-friendly materials, which is in line with energy policies and sustainability protocols. The paper supports the decision making process that takes many variables into account at the building design stage.

Description: This study aims to analyze the global trends of energy mix and energy transition from a chronological view (from Y1995 to Y2015) and identify the actual results based on the empirical findings. It sets up a measurement framework of energy mix (four energy sources: fossil fuel (F), hydroelectric (H), renewable (R), and nuclear (N)), and compares thirty-four Organisation for Economic Cooperation and Development (OECD) countries’ cases through the fuzzy-set ideal type analysis. In short, twelve ideal types of energy mix of the thirty-four OECD countries were derived in Y1995; eleven ideal types in Y2000, thirteen ideal types in Y2005, twelve ideal types in Y2010, and fifteen ideal types in Y2015, respectively. This study particularly reveals the gradual change of the features of energy transition, although an epoch-making trend of overall energy transition in OECD countries is not identified. For example, from1995 to 2010, in the case of Type 7 (F*h*r*N) with a characteristic of ‘pan-conventional energy-centered mix’ having two high features (F, N), and of Type 8 (F*h*r*n), characterized by ‘fossil fuel-centered energy mix’ with one high feature (F), seven to eight countries were steadily included, but in 2015 there was a significant decrease to four countries (solely Type 7). Throughout the five stages from 1995 to 2015, the type with the largest number of countries (20) was Type 10 (f*H*R*n, ‘pan-renewable energy-centered type’) led by hydroelectric (H) and renewable energy sources (R), followed by the second most, Type 12, (f*H*r*N, ‘hydro & nuclear-centered type’, characterized the high features of H and N) with nineteen countries.

Description: Transient stability after islanding is of crucial importance because a controlled islanding strategy is not feasible if transient stability cannot be maintained in the islands created. A new indicator of transient stability for controlled islanding strategies, defined as the critical islanding time (CIT), is presented for slow coherency-based controlled islanding strategies to determine whether all the islands created are transiently stable. Then, the stable islanding interval (SII) is also defined to determine the appropriate time frame for stable islanding. Simulations were conducted on the New England test system–New York interconnected system to demonstrate the characteristics of the critical islanding time and stable islanding interval. Simulation results showed that the answer for when to island could be easily reflected by the proposed CIT and SII indicators. These two indicators are beneficial to power dispatchers to keep the power systems transiently stable and prevent widespread blackouts.

Description: The ever increasing fuel demands and the limitations of oil reserves have motivated research of renewable and sustainable energy resources to replace, even partially, fossil fuels, which are having a serious environmental impact on global warming and climate change, excessive greenhouse emissions and deforestation. For this reason, an alternative, renewable and biodegradable combustible like biodiesel is necessary. For this purpose, waste cooking oil is a potential replacement for vegetable oils in the production of biodiesel. Direct transesterification of vegetable oils was undertaken to synthesize the biodiesel. Several variables controlled the process. The alkaline catalyst that is used, typically sodium hydroxide (NaOH) or potassium hydroxide (KOH), increases the solubility and speeds up the reaction. Therefore, the methodology that this study suggests for improving the biodiesel production is based on computing techniques for prediction and optimization of these process dimensions. The method builds and selects a group of regression models that predict several properties of biodiesel samples (viscosity turbidity, density, high heating value and yield) based on various attributes of the transesterification process (dosage of catalyst, molar ratio, mixing speed, mixing time, temperature, humidity and impurities). In order to develop it, a Box-Behnken type of Design of Experiment (DoE) was designed that considered the variables that were previously mentioned. Then, using this DoE, biodiesel production features were decided by conducting lab experiments to complete a dataset with real production properties. Subsequently, using this dataset, a group of regression models—linear regression and support vector machines (using linear kernel, polynomial kernel and radial basic function kernel)—were constructed to predict the studied properties of biodiesel and to obtain a better understanding of the process. Finally, several biodiesel optimization scenarios were reached through the application of genetic algorithms to the regression models obtained with greater precision. In this way, it was possible to identify the best combinations of variables, both independent and dependent. These scenarios were based mainly on a desire to improve the biodiesel yield by obtaining a higher heating value, while decreasing the viscosity, density and turbidity. These conditions were achieved when the dosage of catalyst was approximately 1 wt %.

Description: In this paper, the effect of some geometrical parameters on the steady state average temperature of the stator core, the winding and the permanent magnets of the yokeless and segmented armature (YASA) axial flux permanent magnet synchronous machine (AFPMSM) is studied. The geometrical parameters selected for the study are the air gap length, the inward heat extraction fin thickness and the permanent magnet thickness. These parametric studies make it possible to obtain a better trade-off between power density and efficiency. These investigations are very helpful in correlating the values of the geometrical parameters to some specific desired performance criteria like not going below some desired minimum efficiency, limiting the temperature of specific part to some maximum value for maximization of lifetime and also determination of the allowed speed range to limit the temperatures lower than the critical values. This is important specifically for the synchronous machines due to the fact that the speed value affects both the losses and the heat transfer convection coefficients. The air gap length has a direct effect on the overall machine losses and the air gap convection coefficient and hence on the temperature of the machine. As the fins are between the stator windings, a thicker fin reduces the space for copper windings and hence increases the losses, but at the same time improves heat evacuation. In addition, the effect on the temperature is studied of the speed variation, which influences both the losses and the convection coefficients of the machine. Every study is made based on coupled electromagnetic and thermal models. The results are obtained from analytical electromagnetic and thermal models verified by finite element simulations and validated experimentally on a 4 kW yokeless and segmented armature axial flux machine.

Description: The crude distillation unit (CDU) is one of the most energy-intensive processes of a petroleum refinery. The composition of crude is subject to change on regular basis. The uncertainty in crude oil composition causes wastage of a substantial amount of energy in the CDU operation. In this study, a novel approach based on a multi-output artificial neural networks (ANN) model was devised to cope with variations (uncertainty) in crude composition. The proposed method is an extended version of another method of cut-point optimization based on hybridization of Taguchi and genetic algorithm. A data comprised of several hundred variations of crude compositions and their optimized cut point temperatures, derived from the hybrid approach, was used to train the ANN model. The proposed method was validated on a simulated CDU flowsheet for a Pakistani crude, i.e., Zamzama. The proposed method is faster and computationally less expensive than the hybrid method. In addition, it can efficiently predict optimum cut point temperatures for any variant of the crude composition.

Description: It is widely accepted that the mechanical properties and failure behaviours of a rock mass are largely dependent upon the geometrical and mechanical properties of discontinuities. The effect of joint elasticity on the failure behaviours of rock masses is investigated using a discrete element model, namely, the synthetic rock mass model. Here, uniaxial compression tests of the numerical model are carried out for the rock mass model with a persistent joint to analyse the role of joint elasticity in the failure process with various joint orientations, β. A strong correlation between the joint elasticity and failure strength is found from the simulation results: a positive relationship when the joint orientation β 〈 φ j ; a negative relationship when the joint orientation φ j 〈 β 〈 90 ° ; and a very limited effect when the joint orientation β = 90 ° . Additionally, it is shown that the joint elasticity is the governing factor in the transition of failure modes, especially from the sliding failure mode along the joint to the mixed sliding-tensile failure mode.

Description: Maximum Power Point Tracking (MPPT) enables photovoltaic (PV) systems to extract as much solar energy as possible. Depending on which type of controller is used, PV systems can be classified as centralized MPPT (CMPPT) or decentralized MPPT (DMPPT). In substring-level systems, it is known that the energy yield of DMPPT can outweigh the power electronics cost. At the substring level, it is usually assumed that the PV curve exhibits a single peak, even under partial shading. Thus, the control algorithms for DMPPT are usually less complicated than those employed in CMPPT systems. This paper provides a comprehensive review of four simple DMPPT algorithms, which are perturb and observe (P&O), incremental conductance (INC), golden section search (GSS), and Newton’s quadratic interpolation (NQI). The comparison of these algorithms are done from the perspective of numerical analysis. Guidelines on how to set initial conditions and convergence criteria are thoroughly explained. This is of great interest to PV engineers when selecting algorithms for use in MPPT implementations. In addition, various problems that have never previously been identified before are highlighted and discussed. For instance, the problems of NQI trap is identified and methods on how to mitigate it are also discussed. All the algorithms are tested under various conditions including static, dynamic, and rapid changes of irradiance. Both simulation and experimental results indicate that P&O and INC are the best algorithms for DMPPT.

Description: The early detection of defective lithium-ion batteries in cellular phones is critical due to the rapid increase in popularity and mass production of cellular phones. It is essential for manufacturers to design an optimal burn-in policy to differentiate between normal and weak batteries in short cycles prior to shipping them to the marketplace. A novel approach to determine the optimal burn-in policy using a feature selection strategy and relevance vector machine (RVM) is proposed. The sequential floating forward search (SFFS) is used as the feature selection method to find an optimal feature subset from the entire sequence of the batteries’ quality characteristics while preserving the original variables. Given the selected feature subset, the RVM is applied to classify batteries into two groups and simultaneously obtain the posterior probabilities. To achieve better discrimination performance with less risk, a new characteristic is extracted from the discharge profile. Subsequently, an optimization cost model is developed by introducing a classification instability penalty to ensure the stability of the optimal number of burn-in cycles. A case study utilizing cellular phone lithium-ion batteries randomly selected from manufactured lots is presented to illustrate the proposed methodology. Furthermore, we conduct a comparison with the cumulative degradation (CD) method and non-cumulative degradation (NCD) method based on the Wiener process. The results show that our proposed burn-in test method performs better than comparable methods.

Description: Air heaters are commonly used devices in steam power plants. In base-loaded conventional power plants, air heaters usually use flue gases for air heating. In this paper, the air heater from a marine steam propulsion plant is analyzed, using superheated steam as a heating medium. In a marine propulsion plant, flue gases from steam generator are not hot enough for the air heating process. In a wide range of steam system loads, the analyzed steam air heater has low energy power losses and high energy efficiencies, ranging from 98.41% to 99.90%. Exergy analysis of the steam air heater showed that exergy destruction is quite high, whereas exergy efficiency ranged between 46.34% and 67.14%. Air heater exergy destruction was the highest, whereas exergy efficiency was the lowest at the highest steam system loads, which was an unexpected occurrence because the highest loads can be expected in the majority of marine steam plant operations. The change in the ambient temperature significantly influences steam air heater exergy efficiency. An increase in the ambient temperature of 10 °C reduces analyzed air heater exergy efficiency by 4.5%, or more, on average.

Description: Brine-dependent recovery, which involves injected water ionic composition and strength, has seen much global research efforts in the past two decades because of its benefits over other oil recovery methods. Several studies, ranging from lab coreflood experiments to field trials, indicate the potential of recovering additional oil in sandstone and carbonate reservoirs. Sandstone and carbonate rocks are composed of completely different minerals, with varying degree of complexity and heterogeneity, but wettability alteration has been widely considered as the consequence rather than the cause of brine-dependent recovery. However, the probable cause appears to be as a result of the combination of several proposed mechanisms that relate the wettability changes to the improved recovery. This paper provides a comprehensive review on laboratory and field observations, descriptions of underlying mechanisms and their validity, the complexity of the oil-brine-rock interactions, modeling works, and comparison between sandstone and carbonate rocks. The improvement in oil recovery varies depending on brine content (connate and injected), rock mineralogy, oil type and structure, and temperature. The brine ionic strength and composition modification are the two major frontlines that have been well-exploited, while further areas of investigation are highlighted to speed up the interpretation and prediction of the process efficiency.

Description: This study investigates the asymmetric impacts of oil price changes on inflation in Algeria, Angola, Libya, and Nigeria. Three different kinds of oil price data were applied in this study: the actual spot oil price of individual countries, the OPEC reference basket oil price, and an average of the Brent, WTI, and Dubai oil price. Autoregressive distributed lag (ARDL) dynamic panels were used to estimate the short- and long-term impacts. Also, we partitioned the oil price into positive and negative changes to capture asymmetric impacts and found that both the positive and negative oil price changes positively influenced inflation. However, the impact was found to be more significant when the oil prices dropped. We also found that the money supply, the exchange rate, and the gross domestic product (GDP) are positively related to inflation, while food production is negatively related to inflation. Accordingly, policy-makers should be cautious when formulating policies between the positive and negative changes in oil prices, as it was shown that inflation increased when the oil price dropped. Additionally, the use of a contractionary monetary policy would help to reduce the inflation rate. Lastly, we suggest that the government should encourage domestic food production, both in quantity and quality, to reduce inflation.

Description: Eucalyptus biomass was studied as a feedstock for sugars release using an alkaline extrusion plus a neutralization-based pretreatment. This approach would be a first step in a bioconversion process aimed at obtaining fuel bioethanol from eucalyptus biomass. The best operation conditions of extrusion (screw speed, temperature, liquid to solid ratio and NaOH amount) that lead to an effective destructuration of lignocellulose and enhanced sugar release were investigated. Two process configurations, with and without filtration inside the extruder, were tested. In the case without filtration, washed and not washed extrudates were compared. It was demonstrated that filtration step was convenient to remove inorganic salts resulting from neutralization and to promote the mechanical effect of extrusion, but limitations in the machine used in the work prevented testing of temperatures above 100 °C using this configuration. In the no filtration strategy, a temperature of 150 °C allowed attaining the highest glucan and xylan conversion rates by enzymatic hydrolysis of extruded biomass, almost 40% and 75%, respectively, of the maximum yield that could be attained if all carbohydrates contained in raw eucalyptus were converted to sugars. Some of the mechanisms and individual effects underlying alkaline extrusion of eucalyptus were figured out in this work, providing guidelines for a successful pretreatment design that needs to be further studied.

Description: Since it first appeared in literature in the early nineties, the Circular Economy (CE) has grown in significance amongst academic, policymaking, and industry groups. The latest developments in the CE field have included the interrogation of CE as a paradigm, and its relationship with sustainability and other concepts, including iterative definitions. Research has also identified a significant opportunity to apply circular approaches to our rapidly changing industrial system, including manufacturing processes and Industry 4.0 (I4.0) which, with data, is enabling the latest advances in digital technologies (DT). Research which fuses these two areas has not been extensively explored. This is the first paper to provide a synergistic and integrative CE-DT framework which offers directions for policymakers and guidance for future research through a review of the integrated fields of CE and I4.0. To achieve this, a Systematic Literature Review (SLR; n = 174) of the empirical literature related to digital technologies, I4.0, and circular approaches is conducted. The SLR is based on peer-reviewed articles published between 2000 and early 2018. This paper also summarizes the current trends in CE research related to manufacturing. The findings confirm that while CE research has been on the increase, research on digital technologies to enable a CE is still relatively untouched. While the “interdisciplinarity” of CE research is well-known, the findings reveal that a substantial percentage is engineering-focused. The paper concludes by proposing a synergistic and integrative CE-DT framework for future research developed from the gaps in the current research landscape.

Description: Multiphysics modeling permits a detailed investigation of complex physical interactions and heterogeneous performance in multiple electro-active layers of a large-format Li-ion cell. For this purpose, a novel 3D multiphysics model with high computational efficiency was developed to investigate detailed multiphysics heterogeneity in different layers of a large-format pouch cell at various discharge rates. This model has spatial distribution and temporal evolution of local electric current density, solid lithium concentration and temperature distributions in different electro-active layers, based on a real pouch cell geometry. Other than previous models, we resolve the discharge processes at various discharge C-rates, analyzing internal inhomogeneity based on multiple electro-active layers of a large-format pouch cell. The results reveal that the strong inhomogeneity in multiple layers at a high C-rate is caused by the large heat generation and poor heat dissipation in the direction through the cell thickness. The thermal inhomogeneity also strongly interacts with the local electrochemical and electric performance in the investigated cell.

Description: Peak current-mode control is widely used in power converters and involves the use of an external compensation ramp to suppress undesired behaviors and to enhance the stability range of the Period-1 orbit. A boost converter uses an analytical expression to find a compensation ramp; however, other more complex converters do not use such an expression, and the corresponding compensation ramp must be computed using complex mechanisms. A boost-flyback converter is a power converter with coupled inductors. In addition to its high efficiency and high voltage gains, this converter reduces voltage stress acting on semiconductor devices and thus offers many benefits as a converter. This paper presents an analytical expression for computing the value of a compensation ramp for a peak current-mode controlled boost-flyback converter using its simplified model. Formula results are compared to analytical results based on a monodromy matrix with numerical results using bifurcations diagrams and with experimental results using a lab prototype of 100 W.

Description: The energy management system (EMS) of a microgrid often presents a complex structure and a large number of control functions, which must be validated to ensure a reliable and optimal operation of the microgrid. Control system validation is typically performed by using hardware-in-the-loop (HIL) architectures in which the microgrid is simulated in real time and interfaced with the actual system under test. The simulation must ensure both an accurate representation of the microgrid and a reliable replica of the field communication of the EMS with all the control devices. In this paper, an overview of the various HIL architectures proposed in the literature is firstly outlined. Then, an HIL validation facility is presented and used to validate the EMS of an industrial microgrid. Finally, some results of the validation tests are reported to give evidence of the effectiveness of the proposed facility. In the proposed architecture, the soft real-time digital simulator of the microgrid is interfaced with the actual EMS using the same communication system and protocol as on the field. The main advantages of the proposed testing facility are: (i) the use of commercial PCs and the absence of dedicated interface modules, resulting in inexpensive hardware components; (ii) the capability to validate both control and communication functions of the EMS; (iii) the applicability to microgrids of different types (industrial, commercial, residential), as well as of various dimensions, including large microgrids; (iv) the easiness in changing the microgrid and the EMS under validation by only software modifications of the simulator tasks and of the exchange interface. As drawbacks, the proposed testing facility presents the need to adapt the software interface between EMS and the field to the EMS under test and the possibility of testing only the EMS functions and not fast-acting local controllers of the microgrid such as the protection systems.

Description: The building sector is responsible for a substantial part of the energy consumption and corresponding CO2 emissions. The European Union has consequently developed various directives, among which the updated Energy Performance of Buildings Directive 2018/844/EU stands out, aiming at minimizing the energy demand in buildings, improving the energy efficiency of their facilities and integrating renewable energies. The objective of the present study was to develop an analysis on the energy performance, related CO2 emissions and operating costs of the renewable energy technologies implemented within a multipurpose near Zero Energy Building (nZEB). The target building is an existing nZEB called LUCIA, located in Valladolid (Spain). Monitoring data provides the required information on the actual needs for electricity, cooling and heating. It is equipped with solar energy photovoltaic systems, a biomass boiler and a geothermal Earth to Air Heat Exchanger (EAHX) intended for meeting the ventilation thermal loads. All systems studied show favourable performances, but depend significantly on the particular characteristics of the building, the control algorithm and the climate of the location. Hence, design of these strategies for new nZEBs must consider all these factors. The combined use of the PhotoVoltaic PV System, the biomass and the EAHX reduces the CO2 emissions up to 123 to 170 tons/year in comparison with other fuels, entailing economic savings from the system operation of up to 43,000–50,000 €/year.

Description: Recent advances in modeling primary atomization in order to enable accurate practical-scale jet spray simulation are reviewed. Since the Eulerian–Lagrangian method is most widely used in academic studies and industrial applications, in which the continuous gas phase is treated in the Eulerian manner and droplets are calculated as Lagrangian point particles, the main focus is placed on improvement within this framework, especially focusing on primary atomization where modeling is the weakest. First, limitations of the conventional methods are described and then novel modeling proposals intended to tackle these issues are covered. These new modeling proposals include the Eulerian surface density approach, and the hybrid Eulerian surface/Lagrangian subgrid droplet generation approach. Compared to conventional simple yet sometimes non-physical models, recent models try to include more physical findings in primary atomization which have been obtained through experiments or direct numerical simulation (DNS). Model accuracy ranges from one that still needs some adjustment using experimental or DNS data to one which is totally self-closed so that no parameter tuning is necessary. These models have the potential to overcome the long-recognized bottleneck in primary atomization modeling and thus to improve the accuracy of whole spray simulation, and may greatly help to improve the spray design for higher combustion efficiency.

Description: China faces significant challenges related to global warming caused by CO2 emissions, and the power industry is a large CO2 emitter. The decomposition and accurate forecasting of CO2 emissions in China’s power sector are thus crucial for low-carbon outcomes. This paper selects seven socio-economic and technological drivers related to the power sector, and decomposes CO2 emissions based on two models: the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model and the partial least square (PLS) model. Distinguished from previous research, our study first compares the effects of eliminating the multicollinearity of the PLS model with stepwise regression and ridge regression, finding that PLS is superior. Further, the decomposition results show the factors’ absolute elasticity coefficients are population (2.58) 〉 line loss rate (1.112) 〉 GDP per capita (0.669) 〉 generation structure (0.522) 〉 the urbanization level (0.512) 〉 electricity intensity (0.310) 〉 industrial structure (0.060). Meanwhile, a novel hybrid PLS-Grey-Markov model is proposed, and is verified to have better precision for the CO2 emissions of the power sector compared to the selected models, such as ridge regression-Grey-Markov, PLS-Grey-Markov, PLS-Grey and PLS-BP (Back propagation neutral network model). The forecast results suggest that CO2 emissions of the power sector will increase to 5102.9 Mt by 2025. Consequently, policy recommendations are proposed to achieve low-carbon development in aspects of population, technology, and economy.

Description: Accurate wind speed forecasting is a significant factor in grid load management and system operation. The aim of this study is to propose a framework for more precise short-term wind speed forecasting based on empirical mode decomposition (EMD) and hybrid linear/nonlinear models. Original wind speed series is decomposed into a finite number of intrinsic mode functions (IMFs) and residuals by using the EMD. Several popular linear and nonlinear models, including autoregressive integrated moving average (ARIMA), support vector machine (SVM), random forest (RF), artificial neural network with back propagation (BP), extreme learning machines (ELM) and convolutional neural network (CNN), are utilized to study IMFs and residuals, respectively. An ensemble forecast for the original wind speed series is then obtained. Various experiments were conducted on real wind speed series at four wind sites in China. The performance and robustness of various hybrid linear/nonlinear models at two time intervals (10 min and 1 h) are compared comprehensively. It is shown that the EMD based hybrid linear/nonlinear models have better accuracy and more robust performance than the single models with/without EMD. Among the five hybrid models, EMD-ARIMA-RF has the best accuracy on the whole for 10 min data, and the mean absolute percentage error (MAPE) is less than 0.04. However, for the 1 h data, no model can always perform well on the four datasets, and the MAPE is around 0.15.

Description: Overtime, in the electricity sector, there has been a technological transfer to renewable electricity generation. With this change, processes, in the economic and availability terms, are expected to improve. In this new paradigm, society demands electricity without an impact on the environment and with the lowest possible cost. The wind power (WP) integration appears in this evolution process by achieving important technological advances, supporting in 2017 a growth of 44% of new projects in Europe, higher than any other renewable technology. However, the renewable energy sources (RES) integration in the electricity networks still presents technical difficulties and challenges, leading to challenges in the electricity markets (EMs). Therefore, this work evaluates the importance of WP and its influence on the Iberian Electricity Market (MIBEL), at the level of the intraday electricity spot market (IESM). This is an innovative study because literature usually focuses on day-ahead WP impact and this study focuses on intraday markets, which are closer to the consumption periods. The goal was to make an analysis on the impacts when betting on WP sources, in order to improve the market interaction with WP integration, considering as criteria the consumer satisfaction, in terms of lower electricity prices and WP availability. For this study, the market bids registered by the Iberian Electricity Market Operator (OMIE), from 2015 to 2017, ran over a new market simulator, specially developed for this proposal, considering a virtual market condition, but not considering the bids made by WP producers. The comparison of the results allowed the evaluation of the WP influence on the EM quantitative, which is noteworthy.

Description: Recently, integrated energy systems have become a new type of energy supply model. It is clear that integrated energy systems can improve energy efficiency and reduce costs. However, the use of a battery energy storage system (BESS) as a backup power source will affect the operating costs of a regional integrated energy system (RIES) in different situations. In this paper, a regional integrated energy system including wind turbines, photovoltaics, gas turbines and battery energy storage was introduced. In order to obtain the minimum operation cost, an operation optimization model was built. The schedule plans of each unit were optimized by a moth flame optimization (MFO) algorithm. Finally, three different scenarios were proposed for the simulation optimization. The simulation optimization results show that when the BESS is used as a backup power source, the operating cost of the system and the resulting pollutant emissions are less than the diesel generator (DG) set. Therefore, it is worthwhile to use BESS instead of DG as the backup power source in RIES.

Description: Solar power’s variability makes managing power system planning and operation difficult. Facilitating a high level of integration of solar power resources into a grid requires maintaining the fundamental power system so that it is stable when interconnected. Accurate and reliable forecasting helps to maintain the system safely given large-scale solar power resources; this paper therefore proposes a probabilistic forecasting approach to solar resources using the R statistics program, applying a hybrid model that considers spatio-temporal peculiarities. Information on how the weather varies at sites of interest is often unavailable, so we use a spatial modeling procedure called kriging to estimate precise data at the solar power plants. The kriging method implements interpolation with geographical property data. In this paper, we perform day-ahead forecasts of solar power based on the probability in one-hour intervals by using a Naïve Bayes Classifier model, which is a classification algorithm. We augment forecasting by taking into account the overall data distribution and applying the Gaussian probability distribution. To validate the proposed hybrid forecasting model, we perform a comparison of the proposed model with a persistence model using the normalized mean absolute error (NMAE). Furthermore, we use empirical data from South Korea’s meteorological towers (MET) to interpolate weather variables at points of interest.

Description: The ternary pH buffer system with ammonia-carbonates-volatile fatty acids (VFAs) is essential to anaerobes for bioenergy recovery via anaerobic digestion (AD). However, ammonia and VFAs are recognized as potential inhibitors that depress methanogenesis. In this study, biochemical conversion and the microbial community in batch AD at total solid (TS) from 4% to 14% were investigated to reveal their response to the ternary pH buffer system. The rapid ammonia release, probably promoted by Anaerosphaera and Eubacterium inferred from the concurrent peak of their relative abundance, triggered total ammonia (TAN) inhibition with the accumulation of VFAs in the start-up stage of high solid AD (HSAD, TS ≥ 8%). Along with evolution of the microbial community to resist high TAN and VFAs, methanogenesis recovered with improved degradation of VFAs and reduction of COD. When exposed to 3500 mg·N·L−1 TAN at 8% TS, aceticlastic Methanosarcina became dominant first and then together with hydrogenotrophic Methanoculleus, achieved the optimal biochemical conversion. While in HSAD at 11–14% TS, the main pathway of methanogenesis appeared to have shifted from the aceticlastic pathway to the hydrogenotrophic pathway, as inferred by changes in the relative abundance of methanogens, and this could have been induced by the increasing concentration of high free ammonia (FAN, ≥588 mg·N·L−1). Although the anaerobes had acclimatized to high TAN, the propionate-oxidizing bacteria and acetate-oxidizing bacteria might have again been inhibited by high FAN, frustrating the H2 supply for FAN-tolerant Methanoculleus and causing an 8.2–11.3% depression of COD reduction (mainly propionate residual).

Description: This paper assesses the long-term wind energy potential at three selected sites, namely Mersing and Kijal on the east coast of peninsular Malaysia and Kudat in Sabah. The influence of the El Niño-Southern Oscillation on reanalysis and meteorological wind data was assessed using the dimensionless median absolute deviation and wavelet coherency analysis. It was found that the wind strength increases during La Niña events and decreases during El Niño events. Linear sectoral regression was used to predict the long-term wind speed based on the 35 years of extended Climate Forecast System Reanalysis data and 10 years of meteorological wind data. The long-term monthly energy production was computed based on the 1.5 MW Goldwind wind turbine power curve. The measured wind data were extrapolated to the selected wind turbine default hub height (70 m.a.s.l) by using the site-specific power law indexed. The results showed that the capacity factor is higher during the Northeast monsoon (21.32%) compared to the Southwest monsoon season (3.71%) in Mersing. Moreover, the capacity factor in Kijal is also higher during the Northeast monsoon (10.66%) than during the Southwest monsoon (5.19%). However, in Kudat the capacity factor during the Southwest monsoon (36.42%) is higher compared to the Northeast monsoon (24.61%). This is due to the tail-effect of tropical storms that occur during this season in the South China Sea and Pacific Ocean.

Description: China has accelerated the pace of shale gas development from 2010. A series of policies were issued by the Chinese government to motivate and regulate shale gas exploration and exploitation. In order to investigate the effectiveness of these policies and provide reference to the policymakers, the most relevant policies from 2010 to 2016 were collected and analyzed. Our study summarized that, in total, eight government agencies issued 25 related policies, which cover all the main problems that impede China’s shale gas industry. With the aid of these policies, the approved research and development (R&D) funds exceed 350 million Chinese yuan (CNY) ($55 million), and over 80 domestic companies participated in exploration rights bidding and nine foreign companies initiated thirteen international cooperation projects. In 2016, China’s shale gas production reached 7.88 × 109 m3, ranking third in the world. However, these policies still have some shortcomings, such as low environmental concerns, weak financial stimulus, and inefficient implementation. Therefore, we suggest that future policy should put particular emphasis on (1) formulating special environmental regulations and determining development scale based on water resource; (2) providing detailed implementation plans and maintaining stable subsidy; (3) enhancing communication and supervision; and (4) establishing a public big data platform.

Description: Several thousand metric tonnes of aquatic biomass are removed from water bodies every year, so that these waters can continue to be used for ship and boat traffic and for leisure activities. The mowed material is generally disposed off without any further use. Therefore, the crop properties of samples from 39 weed control measures all over Germany were examined to assess the suitability of aquatic plant biomass as a substrate for anaerobic digestion systems. Analysis of the crop samples consisted of the identification of plant species and the evaluation of sediment contents and concentrations of macroelements. The methane yield was determined for selected aquatic plants. Analysis revealed a carbon/nitrogen ratio (C/N) of between 10 and 20 in 74% of samples. The concentrations of nitrogen and phosphorous in the samples were comparable to grass silages. With regard to heavy metal concentrations, the threshold values for biowaste for nickel, zinc, and cadmium were exceeded in three samples. There were no significant seasonal differences in substrate characteristics and qualities. The specific methane yields of individual aquatic plants were between 142 and 372 LCH4/kg volatile solids (VS). The results of this study showed that aquatic macrophytes can be used as substrates in anaerobic digestion plants without any restrictions.

Description: Research on the safety of powerhouse in a hydropower station is mostly concentrated on the vibration of machinery structure and concrete structure within a single unit. However, few studies have been focused on the vibration transmission among units. Due to the integrity of the powerhouse and the interaction, it is necessary to study the vibration transmission mechanism of powerhouse structure among units. In this paper, field structural vibration tests are conducted in an underground powerhouse of a hydropower station on Yalong River. Additionally, the simplified mechanical models are established to explain the transmission mechanism theoretically. Moreover, a complementary finite element (FE) model is built to replicate the testing conditions for comprehensive analysis. The field tests results show that: (1) the transmission of lateral-river vibration is greater than those of longitude-river vibration and vertical vibration; (2) the vibration transmission of the vibrations that is caused by the low frequency tail fluctuation is basically equal to that of the vibrations caused by rotation of hydraulic generator. The transmission mechanism is demonstrated by the simplified mechanical models and is verified by the FE results. This study can provide guidance for further research on the vibration of underground powerhouse structure.

Description: In this paper, we consider partial path selection (PPS) for a multi-hop decode-and-forward cooperative system with limited channel state information (CSI) feedback, where the PPS utilizes local CSI only for a subset of hops on each of all independent paths between a source and a destination to reduce the energy consumption for CSI feedback. To enhance the end-to-end performance of the PPS, we propose a novel PPS method with local CSI chosen by the correlation between the end-to-end signal-to-noise ratios (SNRs) based on global and local CSI under Nakagami-m fading channels. For each path, we pick a subset of hops to report CSI with the highest correlation for a given CSI feedback overhead requirement, which can achieve the similar end-to-end outage probability to the best path selection with global CSI. We provide an exact and closed-form expression for the SNR correlation coefficient and present an impact of the SNR correlation on the end-to-end outage probability.

Description: Prediction of the non-linear flow in porous media is still a major scientific and engineering challenge, despite major technological advances in both theoretical and computational thermodynamics in the past two decades. Specifically, essential controls on non-linear flow in porous media are not yet definitive. The principal aim of this paper is to develop a meaningful and reasonable quantitative model that manifests the most important fundamental controls on low velocity non-linear flow. By coupling a new derivative with fractional order, referred to conformable derivative, Swartzendruber equation and modified Hertzian contact theory as well as fractal geometry theory, a flow velocity model for porous media is proposed to improve the modeling of Non-linear flow in porous media. Predictions using the proposed model agree well with available experimental data. Salient results presented here include (1) the flow velocity decreases as effective stress increases; (2) rock types of “softer” mechanical properties may exhibit lower flow velocity; (3) flow velocity increases with the rougher pore surfaces and rock elastic modulus. In general, the proposed model illustrates mechanisms that affect non-linear flow behavior in porous media.

Description: Many African countries have vast biomass resources that could serve as feedstock for methane production through the adoption of commercial biogas plants. However, due to many inhibiting factors, these resources are under-utilised. This article reviews commercial biogas systems that treat organic waste from municipalities, large livestock farms, large plantations/crop farms, food/beverage production facilities, and other industries, to identify essential lessons which African countries could use to develop/disseminate such biogas systems. The review identified the critical barriers to commercial biogas development to be high initial capital costs, weak environmental policies, poor institutional framework, poor infrastructure and a general lack of willpower to implement renewable energy policies and set challenging targets. In African countries where feed-in-tariffs, quota obligations and competitive bidding programmes have been instituted, implementation has been poor, and most state-owned utilities have been unsupportive. Using knowledge from more experienced countries such as Germany and China, some key lessons have were identified. Among the key lessons is the need to institute and enforce environmental management policies to ensure that waste from medium and large livestock farms and industries are not disposed of indiscriminately, a tool China has recently used to promote commercial biogas plants to a high degree of success.

Description: Energy originating in tidal and ocean currents appears to be more intense and predictable than other renewables. In this area of research, the Tidal Stream Generator (TSG) power plant is one of the most recent forms of renewable energy to be developed. The main feature of this energy converter is related to the input resource which is the tidal current speed. Since its behaviour is variable and with disturbances, these systems must be able to maintain performance despite the input variations. This article deals with the design and control of a tidal stream converter system. The Fuzzy Gain Scheduling (FGS) technique is used to control the blade pitch angle of the turbine, in order to protect the plant in the case of a strong tidal range. Rotational speed control is investigated by means of the back-to-back power converters. The optimal speed is provided using the Maximum Power Point Tracking (MPPT) strategy to harness maximum power from the tidal speed. To verify the robustness of the developed methods, two scenarios of a disturbed tidal resource with regular and irregular conditions are considered. The performed results prove the output power optimization and adaptive change of the pitch angle control to maintain the plant within the tolerable limits.

Description: Smart meters are applied to the smart grid to report instant electricity consumption to servers periodically; these data enable a fine-grained energy supply. However, these regularly reported data may cause some privacy problems. For example, they can reveal whether the house owner is at home, if the television is working, etc. As privacy is becoming a big issue, people are reluctant to disclose this kind of personal information. In this study, we analyzed past studies and found that the traditional method suffers from a meter failure problem and a meter replacement problem, thus we propose a smart meter aggregation scheme based on a noise addition method and the homomorphic encryption algorithm, which can avoid the aforementioned problems. After simulation, the experimental results show that the computation cost on both the aggregator and smart meter side is reduced. A formal security analysis shows that the proposed scheme has semantic security.

Description: The hydropower station with a super long headrace tunnel is a significant development type for hydropower energy. By constructing a super long headrace tunnel, the huge natural water fall head can be utilized to generate more electricity. With the development of hydropower energy, a hydropower station with a super long headrace tunnel becomes more and more competitive. Compared with a hydropower station with a short headrace tunnel, the transient process and control for a hydropower station with a super long headrace tunnel is much more complicated and becomes an intractable challenge. It is well known that the transient process and control is the basis of the design and operation of a hydropower station. To overcome the challenge of the transient process and control, much research has been carried out. This paper provides a systematic review on the latest research progress of the transient process and control for hydropower stations with a super long headrace tunnel. Firstly, two key issues for the transient process and control, i.e., hydraulic design optimization of the surge tank and operation control of unit, are illuminated. Secondly, for both single surge tanks and surge tanks with special types or combinations, the hydraulic design optimization methods are described. The most disadvantageous design and advantageous operation of surge tanks under combined operating conditions are discussed. Thirdly, the stability and regulation quality of the hydro-turbine governing system under isolated and grid-connected operation conditions are presented. Finally, some trends and recommendations for future research directions are made. A research thought for establishing the complete theory and application system of the transient process and control for hydropower stations with a super long headrace tunnel from the perspective of multi-slice and multi-scale is proposed.

Description: In this study, we have built a dual porosity/permeability model through accurately expressing the volumetric strain of matrix and fracture from a three-dimensional method which aims to reveal the reservoir permeability evolution during the process of CO2-enhanced coalbed methane (CO2-ECBM) recovery. This model has accommodated the key competing processes of mechanical deformation and adsorption/desorption induced swelling/shrinkage, and it also considered the effect of fracture aperture and effective stress difference between each medium (fracture and matrix). We then numerically solve the permeability model using a group of multi-field coupling equations with the finite element method (FEM) to understand how permeability evolves temporally and spatially. We further conduct multifaceted analyses to reveal that permeability evolution near the wells is the most dramatic. This study shows that the farther away from the well, the gentler the evolution of permeability. The evolution of reservoir permeability near the injection well (IW) and the production well (PW) are very different, due to the combined effects of effective stress changes and gas adsorption and desorption. Furthermore, adsorption is the main controlling factor for the change of permeability for regions near the IW, while the change in effective stress is the main cause for the change in permeability near the PW. Increasing the injection pressure of CO2 will cause the reservoir permeability to evolve more quickly and dynamically.

Description: The co-pyrolysis of used lubricant oil blended with plastic waste, namely high-density polyethylene (HDPE), polypropylene (PP), and polystyrene (PS), to produce a diesel-like fuel was studied. The proportions of the raw materials were optimized using laboratory scale pyrolysis at atmospheric pressure at a final temperature of 450 °C without a catalyst. The ratios of used lubricant oil (Oil) and plastic waste (Oil:HDPE:PP:PS) investigated were 50:30:20:0, 50:30:0:20, 50:0:30:20, and 50:30:10:10 by weight. It was found that the oil produced using an Oil:HDPE:PP:PS ratio of 50:30:20:0 exhibited most of the properties of standard diesel oil as specified by the Ministry of Energy (Thailand), except for its flash point, which was lower than the standard. Therefore, this proportion was utilized for the scaled-up testing in the co-pyrolysis prototype (10 kg/day). Three reactor temperature ranges (less than 400 °C, 400–425 °C, and 425–450 °C) were studied, and the properties of the oil products were analysed. The oil products produced at 400–425 °C exhibited diesel-like fuel properties.

Description: The Dutch residential sector is locked-in into natural gas for the supply of heat. The expected depletion of national reserves and induced earthquakes in the production area are reasons to aim to escape this lock-in. The Dutch government and key players in the natural gas sector have expressed large green gas ambitions. This paper explores the opportunities and barriers of biomass gasification for green gas production and application in the residential sector. The Technological Innovation Systems and Multi-Level Perspective were applied as sustainability transition frameworks to explore the current technological state of biomass gasification and the developments in the residential sector. Four limitations were observed from a supply perspective; little financial space for demonstration plants, absence of technology specific policy, lagging market developments and insecurities related to biomass availability. On the demand side, clear barriers hampering change are observed, providing large opportunities for green gas. Key players in the natural gas regime take no substantial responsibility, despite their potential ability to contribute to overcoming systemic barriers. Therefore, this research concludes that the current green gas ambitions set by the Dutch government are not feasible and that the government may address this with technology specific policy, substantial research and development subsidies and funding.

Description: Operational activities of gas pipelines are associated with potential hazards and risks that can potentially lead to pipeline failure, including failure of the gas distribution pipeline in existing buildings. Unfortunately, few studies on risk analysis of the gas distribution pipeline in existing buildings have been published. Therefore, this study was conducted to provide a reference for analyzing the risk of pipeline leakage caused by small-scale leakage, large-scale gas release, and gas pipeline rupture in existing buildings in Indonesia not designed for gas installation. The study was performed using the event tree analysis method. The methodology of this study was initiated by identifying the scenario of the case of small-scale leakage, large-scale gas release, or gas pipeline rupture. Then, pivotal events were identified, an event tree diagram was constructed, the event failure of each pivotal event was determined, and the probability value of the outcome risk was calculated. The risk was evaluated in terms of fire, casualties, and gas released. The results of this study showed the highest risk in each scenario which can result in fire, severe casualties, and light poisoning. The highest risk in the small-scale leak scenario had a probability value of 1.5 × 10−3. In the large-scale gas release scenario, the highest risk had a probability value to incur a fireball, severe casualties, and light gas poisoning of 6.0 × 10−4. In the gas pipeline rupture scenario, the highest risk had a probability value of fireball, severe casualties, and light poisoning of 7.0 × 10−4. The probability value of each risk was reduced by the installation of a gas detector and water sprinkler as a barrier.

Description: The knowledge of the actual energy performances of a concentrating photovoltaic and thermal (CPV/T) system with a linear focus optics, allows to evaluate the possibility of adopting this type of system for cogeneration purposes. Hence, the main aim of this paper is the design, realization, setting and modeling of a linear focus CPV/T system in the high concentration field. An experimental linear focus CPV/T plant was created in order to determine its electrical and thermal performance under different working conditions in terms of environment temperature, sunny and cloudy conditions, focal length, etc. Moreover, a theoretical model of the linear focus CPV/T system was also studied. This model evaluates the temperatures of the working fluid that flows in the cooling circuit of the CPV/T system under several operating conditions. The temperatures of the triple junction (TJ) cells, experimentally evaluated referring to different solar radiation and atmospheric conditions, were considered as the input data for the model. The values of the fluid temperature, theoretically and experimentally determined, were thus compared with good agreement. The electrical production of the CPV/T system depends generally on the TJ cell characteristics and the concentration factor, while the thermal production is above all linked to the system configuration and the direct normal irradiance (DNI) values. Hence, in this paper the electric power obtained by the linear-focus CPV/T system was evaluated referring to the cogeneration applications, and it was verified if the TJ cell and the cooling fluid reach adequate temperature levels in this type of system, in order to match the electrical and the thermal loads of a user.

Description: Optimal power flow (OPF) is a non-linear and non-convex problem that seeks the optimization of a power system operation point to minimize the total generation costs or transmission losses. This study proposes an OPF model considering current margins in radial networks. The objective function of this OPF model has an additional term of current margins of the line besides the traditional transmission losses and generations costs, which contributes to thermal stability margins of power systems. The model is a reformulated bus injection model with clear physical meanings. Second order cone program (SOCP) relaxations for the proposed OPF are made, followed by the over-satisfaction condition guaranteeing the exactness of the SOCP relaxations. A simple 6-node case and several IEEE benchmark systems are studied to illustrate the efficiency of the developed results.

Description: In this paper, the study and optimization design of stator coreless axial flux permanent magnet synchronous generators is presented for direct driven variable speed renewable energy generation system applications while considering the requirement of reliability and dynamic performance with unstable input conditions. The dynamic analytical model is developed based on the investigation of the axial flux permanent magnet synchronous generator (AFPMSG) structure and basic electromagnetic equations to find out the relationship between generator parameters and dynamic performance. Simulation via the MATLAB/Simulink platform is carried out to obtain the sensitivity of dynamic performance to generator parameters. An integrated optimization model that takes the key parameters as variables is proposed, aiming to improve the mechanical dynamic performance of AFPMSG. For accurate design, the design procedure is modified by combining the nonlinear iterative genetic algorithm (GA) to perform the calculation. A 3_kW AFPMSG is optimally designed to minimize the output voltage overshooting—the index of dynamic performance for direct driven variable speed generation application. Finally, a three-dimensional (3D) finite element model of the generator is established by Maxwell ANSOFT, and the simulation results confirm the validity of the dynamic performance analysis and optimal design procedure.

Description: Exhaust gas recirculation (EGR) and high-pressure fuel injection are key technologies for reducing diesel engine emissions in the face of reinforced regulations. With the increasing need for advanced EGR technologies to achieve low-temperature combustion and low emission, the adverse etableffects of EGR must be addressed. One of the main problems is fouling of the EGR cooler, which involves the deposition of particulate matter (PM) due to the thermophoretic force between the cooler wall and flow field. A large amount of deposited PM can reduce the effectiveness of the heat exchanger in the EGR cooler and the de-NOx efficiency. In the present study, the effects of the variables that affect EGR cooler fouling are investigated by a comparison of laboratory-based and engine-based experiments. In the laboratory experiment, a soot generator that could readily provide separate control of the variables was used to generate the model EGR gas. Through control of the soot generator, it was possible to perform a parametric study by varying the particle size, the EGR gas flow rate, and the coolant temperature as the dominant parameters. A decrease in these factors caused an increase in the mass of the deposit and a drop in the effectiveness of the heat exchanger, related to fouling of the EGR cooler. In the engine-based experiment, engine-like conditions were provided to analyze real exhaust gas without a soot generator. Different variables were found to induce fouling of the EGR cooler, and the results of the engine-based experiment differed from those of the laboratory experiment. For example, in the engine-based experiment, a decrease in the EGR gas flow rate did not lead to a more pronounced drop in the effectiveness of the heat exchanger because of the increase in the concentration of PM in the EGR gas. This result shows that the conditions of the engine exhaust gas are different from those of the soot generator.

Description: Solar energy is the most clean renewable energy source and has good prospects for future sustainable development. Installation of solar photovoltaic (PV) systems on building rooftops has been the most widely applied method for using solar energy resources. In this study, we developed an approach to simulate the monthly and annual solar radiation on rooftops at an hourly time step to estimate the solar PV potential, based on rooftop feature retrieval from remote sensing images. The rooftop features included 2D rooftop outlines and 3D rooftop parameters retrieved from high-resolution remote sensing image data (obtained from Google Maps) and digital surface model (DSM, generated from the Pleiades satellite), respectively. We developed the building features calculation method for five rooftop types: flat rooftops, shed rooftops, hipped rooftops, gable rooftops and mansard rooftops. The parameters of the PV modules derived from the building features were then combined with solar radiation data to evaluate solar photovoltaic potential. The proposed method was applied in the Chao Yang District of Beijing, China. The results were that the number of rooftops available for PV systems was 743, the available rooftop area was 678,805 m2, and the annual PV electricity potential was 63.78 GWh/year in the study area, which has great solar PV potential. The method to perform precise calculation of specific rooftop solar PV potential developed in this study will guide the formulation of energy policy for solar PV in the future.

Description: In this paper, we investigate energy-efficient multicast precoding for massive multiple-input multiple-output (MIMO) transmission. In contrast with most previous work, where instantaneous channel state information (CSI) is exploited to facilitate energy-efficient wireless transmission design, we assume that the base station can only exploit statistical CSI of the user terminals for downlink multicast precoding. First, in terms of maximizing the system energy efficiency, the eigenvectors of the optimal energy-efficient multicast transmit covariance matrix are identified in closed form, which indicates that optimal energy-efficient multicast precoding should be performed in the beam domain in massive MIMO. Then, the large-dimensional matrix-valued precoding design is simplified into an energy-efficient power allocation problem in the beam domain with significantly reduced optimization variables. Using Dinkelbach’s transform, we further propose a sequential beam domain power allocation algorithm which is guaranteed to converge to the global optimum. In addition, we use the large-dimensional random matrix theory to derive the deterministic equivalent of the objective to reduce the computational complexity involved in sample averaging. We present numerical results to illustrate the near-optimal performance of our proposed energy-efficient multicast precoding for massive MIMO.

Description: Hydrothermal liquefaction (HTL) of biomass is emerging as an effective technology to efficiently valorize different types of (wet) biomass feedstocks, ranging from lignocellulosics to algae and organic wastes. Significant research into HTL has been conducted in batch systems, which has provided a fundamental understanding of the different process conditions and the behavior of different biomass. The next step towards continuous plants, which are prerequisites for an industrial implementation of the process, has been significantly less explored. In order to facilitate a more focused future development, this review—based on the sources available in the open literature—intends to present the state of the art in the field of continuous HTL as well as to suggest means of interpretation of data from such plants. This contributes to a more holistic understanding of causes and effects, aiding next generation designs as well as pinpointing research focus. Additionally, the documented experiences in upgrading by catalytic hydrotreating are reported. The study reveals some interesting features in terms of energy densification versus the yield of different classes of feedstocks, indicating that some global limitations exist irrespective of processing implementations. Finally, techno-economic considerations, observations and remarks for future studies are presented.

Description: This paper proposes the study and analysis of harmonics, energy consumption and power quality of light emitting diode (LED) lamps equipped in building lighting systems. LED lamps with external (LED MR16) and internal (LED light bulb) drivers are investigated using an experimental setup to compare the results. The power quality of both LED lamps is studied by using a power quality meter to measure the generated harmonic currents from various case studies. The case study is divided into four major cases: one LED lamp is turned on with one driver, two LED lamps are turned on using the two drivers, eight LED lamps are turned on with one driver, and eight LED lamps are turned on with the eight drivers. As harmonics are related to total power factor (PF), which affects the energy savings of the building, hence, a filtering circuit to reduce harmonic current has been designed and implemented to improve power quality and/or power factor of the system. The different cases of harmonic filter insertion at the input of an LED lamp’s driver are discussed and then compared with a lighting standard to show the effectiveness of the passive filtering technique used in the studied system. In addition, the obtained result can be applied to both newly built and retrofitted buildings that aim to use LED technology to increase energy efficiency and decrease energy costs, and could be a helpful guide for end-users and manufacturers in addressing and developing LED issues.

Description: In the present work, a crashworthy device for a monopile offshore wind turbine has been proposed, which consists of the inner two-layer rubber torus and the outer thin steel shell. The performance of the crashworthy device against ship impact has been investigated experimentally. Based on the prototype of a 4 MW monopile wind turbine in the East China Sea, the scale ratio of the test model has been designed to be 1/50. The test ship model has been simplified as a “rigid car” equipped with a high-frequency force sensor in the front, which is available for changing the ship mass with different weights. The ship-impact velocity can be accurately controlled by a motion platform driven by a direct current machine. The effect of the key design parameters of the crashworthy device on its anti-impact performance has been tested and compared under typical ship impact cases. The results indicate that the crashworthy device can effectively reduce both the ship impact force and the top nacelle acceleration, and the physical mechanism that has been clarified. The outer thin steel shell can significantly use its structural deformation to absorb the ship impact energy, which is beneficial for reducing the structural damage of the offshore wind turbine (OWT)’s tower. The inner rubber torus can effectively prolong the ship impact duration, which is available for smoothing the impact force. Finally, the porous design for the outer steel shell of the crashworthy device has been proposed and tested.

Description: In this paper we have proposed the simple and effective approach to activation of the low reactivity industrial fuel which can be used immediately inside the furnace. The high-power laser pulses initiates partial gasification of the fuel together with its ultra-fine atomization. The gas-aerosol cloud surrounding the initial coal-water slurry droplet can consist of approximately 10% (after absorption of hundred pulses) of the initial droplet weight. The ratio of the syngas and aerosol weights is like 1:2 when pulse intensity is higher than 8 J/cm 2 . The size and velocity distributions of the ultra-fine aerosol particles were analysed using the original realization of the particle tracking velocimetry technique.

Description: For the dc microgrid system with constant power loads (CPLs), the dc bus voltage can easily cause high-frequency oscillation owing to the complicated impedance interactions. The large line inductance and the CPL-side capacitance will form an undamped LC circuit on the dc bus, which, together with the CPL, will make the system fall into the negative-damping region, thus causing the system instability. To address this problem, a virtual negative inductor (VNI) is built on the source side converter in this paper, which can effectively counteract the large line inductance, thus alleviating the instability problem. Moreover, a nonlinear disturbance observer (NDO) is proposed for estimating the converter output current, which relieves the strong dependence of the proposed VNI strategy on the output current measurement. And the proposed strategy is implemented in a totally decentralized manner, thus alleviating the single-point-failure problem in the central controller. For assuring the optimal parameter value for the proposed stabilizing strategy, a system root-locus diagram based parameter designing approach is adopted. And comparative Nyquist diagram based stability analyses are taken for studying the robustness of the proposed strategy to the system perturbations. Finally, detailed real-time simulations are conducted for validating the effectiveness of the proposed stabilizing strategy.

Description: This paper suggests a daylighting design method by combining a passive approach and advanced software to design external shading devices for daylighting in a classroom. A simplified method to predict and assess the indoor natural illuminance is a prerequisite for designers to design schools with better performance. Recently there has been growing demand for school refurbishment; mainly environmental improvement of classrooms in Korea. However, the passive approach of design has been neglected while the use of advanced simulation software has increased, requiring additional time and cost. Combining passive design methods with up-to-date numerical simulation is explored with shading devices to verify the daylighting distribution and daylight autonomy in classrooms with different orientations and shading forms. Weather tool Autodesk Ecotect, for the shading coefficient, and DaySim software (v3.0), for daylight autonomy, were adopted for the initial and the detail design stage, respectively. The findings support the linked design approaches of passive and advanced software would benefit designers in the strategic design process with further potential for design options and lighting electricity reduction.

Description: The growing amount of distributed generation has brought great uncertainty to power grids. Traditional probabilistic load flow (PLF) algorithms, such as the Monte-Carlo method (MCM), can no longer meet the needs of efficiency and accuracy in large-scale power grids. Latin Hypercube Sampling (LHS) develops a sampling efficiency and solves the correlation problem of distributed generation (DG) access nodes for accuracy analyses. In this paper, a modified Latin Hypercube-Important Sampling method is proposed for higher efficiency and precision by using the importance sampling method before LHS and the Cholesky decomposition method in correlation calculations. The simulation results are presented using a modified IEEE 30-bus system and are compared with traditional MCM and LHS.

Description: Static correction is an essential step in seismic processing and it has an effect on the later steps of seismic processing, including velocity analysis, data stacking, and seismic inversion. During seismic data acquisition, a receiving point usually sets a geophone several times to receive the seismic data. The same geophone cannot be set at the same receiving point every time. If the geophones have different delay time, then the common receiving-point gather (CRG) will have multiple receiver statics. However, the receiver statics of a CRG are considered the same in conventional static correction. In this paper, based on common attitude gather (CAG), a novel static correction method is proposed to analyze the receiver statics of a CRG. Attitude indicates the tilt angles of the three components of a geophone. According to the different attitudes of geophones, CRG can be divided into multiple CAGs. When the difference technique is used to the novel method and the conventional method, the statics are analyzed with CAGs and CRGs, respectively. A field example demonstrates that the proposed method cannot only enhance the continuity of the event in the shot gather, but also smooth the gaps of the event in the CRG. The results suggest that the proposed method can eliminate the effect of differences in delay time of geophones on static correction.

Description: A numerical study was performed to investigate the thermal performance characteristics of an enhanced tube heat exchanger fitted with punched delta-winglet vortex generators. Computational fluid dynamics modeling was applied using the k–ε renormalized group turbulence model. Benchmarking was performed using the results of the experimental study for a similar geometry. Attack angles of 30°, 50°, and 70° were used to investigate the heat transfer and pressure drop characteristics of the enhanced tube. Flow conditions were considered in the turbulent region in the Reynolds number range of 9100 to 17,400. A smooth tube was employed for evaluating the increment in the Nusselt number and the friction factor characteristics of the enhanced tube. The results show that the Nusselt number, friction factor, and thermal performance factor have a similar tendency. The presence of this insert offers a higher thermal performance factor as compared to that obtained with a plain tube. Vortex development in the flow structure aids in generating a vortex flow, which increases convective heat transfer. In addition, as the angle is varied, it is observed that the largest attack angle provides the highest thermal performance factor. The greatest increase in the Nusselt number and friction factor, respectively, was found to be approximately 3.7 and 10 times greater than those of a smooth tube. Through numerical simulations with the present simulation condition, it is revealed that the thermal performance factor approaches the value of 1.1. Moreover, the numerical and experimental values agree well although they tend to be different at high Reynolds number conditions. The numerical and experimental values both show similar trends in the Nusselt number, friction factor, and thermal performance factor.

Description: The gas drainage borehole is a typical hole-containing structure, and its failure is similar to the hole-containing specimen. To study the characteristics of wave velocity and power spectral density of the hole-containing specimens with different moisture content, an ultrasonic test of the hole-containing specimens during destruction was carried out. A waveform with different moisture contents was recorded by the RSM-SY7 system. The wave velocity and power spectral density was calculated to analyze its relationship with moisture content and degree of damage. The results show that the wave velocity of the hole-containing specimens gradually decreases during the destruction. There were 3 stages of attenuation of wave velocity during the destruction, which were stable, slightly reduced, and rapidly decreasing stages. Changes in moisture content would cause changes of duration of the three stages. The power spectral density gradually decreases during the destruction. The moisture content affected the attenuation mode of the power spectral density and the amount of attenuation. In the detecting of the gas borehole, the wave velocity and the power spectral density can be used to locate the damage area. This research provides a theoretical basis for detection engineering.

Description: In this paper, a non-Fourier heat conduction model of ultra-short pulsed laser ablation of metal is established that takes into account the effect of the heat source, laser heating of the target, the evaporation and phase explosion of target material, the formation and expansion of the plasma plume, and interaction of the plasma plume with the incoming laser. Temperature dependent optical and thermophysical properties are also considered in the model due to the properties of the target will change over a wide range during the ultra-short pulsed laser ablation process. The results show that the plasma shielding has a great influence on the process of ultra-short pulsed laser ablation, especially at higher laser fluence. The non-Fourier effect has a great influence on the temperature characteristics and ablation depth of the target. The ultra-short pulsed laser ablation can effectively reduce the heat affected zone compared to nanosecond pulsed laser ablation. The comparison between the simulation results and the experimental results in the literature shows that the model with the plasma shielding and the non-Fourier effect can simulate the ultra-short pulsed laser ablation process better.

Description: Wind power belongs to sustainable and clean energy sources which play a vital role of reducing environment pollution and addressing energy crisis. However, wind power outputs are quite difficult to predict because they are derived from wind speeds, which vary irregularly and greatly all the time. The uncertainty of wind power causes variation of the variables of power grids, which threatens the power grids’ operating security. Therefore, it is significant to provide the accurate ranges of power grids’ variables, which can be used by the operators to guarantee the power grid’s operating security. To achieve this goal, the present paper puts forward the interval power flow with wind farms model, where the generation power outputs of wind farms are expressed by intervals and three types of control modes are considered for imitating the operation features of wind farms. To solve the proposed model, the affine arithmetic-based method and optimizing-scenarios method are modified and employed, where three types of constraints of wind control modes are considered in their solution process. The former expresses the interval variables as affine arithmetic forms, and constructs optimization models to contract the affine arithmetic forms to obtain the accurate intervals of power flow variables. The latter regards active power outputs of the wind farms as variables, which vary in their corresponding intervals, and accordingly builds the minimum and maximum programming models for estimating the intervals of the power flow variables. The proposed methods are applied to two case studies, where the acquired results are compared with those acquired by the Monte Carlo simulation, which is a traditional method for handling interval uncertainty. The simulation results validate the advantages, effectiveness and the applicability of the two methods.

Description: The use of biomass to obtain value-added products has been a good alternative for reducing their environmental impacts. For this purpose, different studies have been carried out focused on the use of agro-industrial waste. One of the most commonly used raw materials has been bagasse obtained from the processing of sugarcane in high quantities in countries like Brazil, India, China, Thailand, Pakistan, Mexico, Colombia, Indonesia, Philippines, and the United States. From 1 ton of sugarcane, 280 kg of bagasse can be obtained. Sugarcane bagasse (SCB) is a waste that is rich in polysaccharides, which makes it a promising raw material for obtaining products under biorefinery concept. The objective of this work was to analyze from the energetic point of view, different biorefinery schemes in which SCB is employed as a raw material. The design and simulation of the different biorefinery schemes is performed in Aspen Plus software. From this software, it was possible to obtain the different mass and energy balances, which are used in the technical and energetic analysis. Exergy is used as a comparison tool for the energy analysis. These analyses allowed for the selection of the best biorefinery configuration from SCB.

Description: This study aims to investigate how overall food supply chain performance (FSCP) often depends on the performance of partners in a sustainable and energy-efficient supply chain. Initially, the study classifies the FSCP and further examines the partner relationships in sustainability-oriented food supply chain (FSC). To do so, the study proposes and formally tests a five-stage performance measurement model. The present research mainly focuses on the Indian food industry. Results highlight significant direct and indirect positive performance relationships between the different FSC stages. The structural equation modeling analysis highlights that producer’s performance positively impacts supplier’s performance, processor’s performance, and distributor’s performance. Moreover, supplier’s performance positively impacts processor’s performance, distributor’s performance, and retailer’s performance, and also processor’s performance positively impacts both distributor’s performance and retailer’s performance. Lastly, distributor’s performance positively impacts retailer’s performance. The study suggests that regular performance improvement at each FSC stage would improve the performance of the next stage players. Most importantly, the direct impact of each partner’s performance is comparatively high on its immediate next partner’s performance. Furthermore, this study will assist practitioners to understand various FSCP measurement issues and make significant improvements in their sustainable and energy-efficient supply chain practices.

Description: The design and construction of roof cutting and blasting is a key part of the roof cutting pressure releasing gob-side entry retaining (RCPRGER) technology. In the existing research, the blasting parameters of roof cutting have been primarily determined by field tests. However, the disadvantages of field tests include a complicated process, which hinders the succession of related procedures, and an unstable roof cutting effect. Therefore, in this work, the authors attempt to use a mathematical analysis method to simplify the design process of the key parameters of roof cutting blasting. First, the mechanics process mechanism of surrounding rocks with roof cutting and pressure releasing is investigated, and the stress evolution process of the surrounding rock is divided into the following six stages: original rock stress state, excavation stress state, supporting stress state, roof cutting stress state, premining stress state, and postmining stress state. Furthermore, the relationship between roof cutting and entry retaining from the perspective of Mohr’s stress circle is discussed. Next, using four typical mines, including the Tashan, Yuanlin, Jinfeng, and Hengyuan coal mines, as examples, the existing design methods of roof cutting and blasting, geological data characteristics of each mine, distribution rule of roof cutting connectivity rate, and explosive charge structure of roof cutting blasting are summarized. Based on these results, the logic of roof cutting blasting design is obtained, the key indices affecting blasting design are determined, and the blasting design is defined as a complex fuzzy problem with multiple factors. Finally, based on the study of the above mechanics mechanism and blasting rule, a three-layer back propagation (BP) neural network, including six input units, nine hidden units, and three output units, is developed with the four typical mines as the sample space. This neural network realizes the rapid determination of the three key parameters pertaining to sealing length, blasthole spacing, and the explosive charge weight of a single hole. Through training, the calculation error is less than 0.48%, which considerably simplifies the design process of the blasting parameters. The charge structure parameters can also be determined according to this method. At present, the construction of this neural network has the shortcomings of limited sample space. This problem can be overcome by supplementing the sample size in the subsequent research and practice, which will improve the efficiency and accuracy of this design method and promote the application and development of the RCPRGER technology. The interdisciplinary research reported in this paper is an attempt that uses an intelligent algorithm to simplify the design process of roof cutting blasting in RCPRGER, and it represents not only an application development of the intelligent algorithm, but also a new step regarding the intelligent design of RCPRGER technology.

Description: The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible Renewable Energies levy (EEG levy) was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering the electricity price and weather forecasts as well as an internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system.

Description: The embedded discrete fracture model (EDFM) combines the advantages of previous numerical models for fractured reservoirs, achieving a good balance between calculation cost and simulation accuracy. In this work, an integrally embedded discrete fracture model (iEDFM) is introduced to further improve the simulation accuracy and expand the application of the model. The iEDFM has a new gridding method that can arbitrarily grid the fractures according to the requirements rather than finely subdividing fracture elements. Then, with a more precise pressure distribution assumption inside the matrix blocks, we are able to obtain a semi-analytic calculation method of matrix-fracture transmissibility applied to iEDFM. Several case studies were conducted to demonstrate the advantage of iEDFM and its applicability for intersecting and nonplanar fractured reservoirs, and a 3D case with a modified dataset from a reported seismic survey could be used to demonstrate the potential application of the iEDFM in real field studies.

Description: An unprecedented opportunity is presented by smart grid technologies to shift the energy industry into the new era of availability, reliability and efficiency that will contribute to our economic and environmental health. Renewable energy sources play a significant role in making environments greener and generating electricity at a cheaper cost. The cloud/fog computing also contributes to tackling the computationally intensive tasks in a smart grid. This work proposes an energy efficient approach to solve the energy management problem in the fog based environment. We consider a small community that consists of multiple smart homes. A microgrid is installed at each residence for electricity generation. Moreover, it is connected with the fog server to share and store information. Smart energy consumers are able to share the details of excess energy with each other through the fog server. The proposed approach is validated through simulations in terms of cost and imported electricity alleviation.

Description: Demand response (DR) has become an effective and critical method for obtaining better savings on energy consumption and cost. Buildings are the potential demand response resource since they contribute nearly 50% of the electricity usage. Currently, more DR applications for buildings were rule-based or utilized a simplified physical model. These methods may not fully embody the interaction among various features in the building. Based on the tree model, this paper presents a novel model based control with a random forest (MBCRF) learning algorithm for the demand response of commercial buildings. The baseline load of demand response and optimal control strategies are solved to respond to the DR request signals during peak load periods. Energy cost saving of the building is achieved and occupant’s thermal comfort is guaranteed simultaneously. A linguistic if-then rules-based optimal feature selection framework is also utilized to redefine the training and test set. Numerical testing results of the Pennsylvania-Jersey-Maryland (PJM) electricity market and Research and Support Facility (RSF) building show that the load forecasting error is as low as 1.28%. The peak load reduction is up to 40 kW, which achieves a 15% curtailment and outperforms rule-based DR by 5.6%.

Description: The Power Take-Off (PTO) system is the key component of a Wave Energy Converter (WEC) that distinguishes it from a simple floating body because the uptake of the energy by the PTO system modifies the wave field surrounding the WEC. Consequently, the choice of a proper PTO model of a WEC is a key factor in the accuracy of a numerical model that serves to validate the economic impact of a wave energy project. Simultaneously, the given numerical model needs to simulate many WEC units operating in close proximity in a WEC farm, as such conglomerations are seen by the wave energy industry as the path to economic viability. A balance must therefore be struck between an accurate PTO model and the numerical cost of running it for various WEC farm configurations to test the viability of any given WEC farm project. Because hydrodynamic interaction between the WECs in a farm modifies the incoming wave field, both the power output of a WEC farm and the surface elevations in the ‘near field’ area will be affected. For certain types of WECs, namely heaving cylindrical WECs, the PTO system strongly modifies the motion of the WECs. Consequently, the choice of a PTO system affects both the power production and the surface elevations in the ‘near field’ of a WEC farm. In this paper, we investigate the effect of a PTO system for a small wave farm that we term ‘WEC array’ of 5 WECs of two types: a heaving cylindrical WEC and an Oscillating Surge Wave Energy Converter (OSWEC). These WECs are positioned in a staggered array configuration designed to extract the maximum power from the incident waves. The PTO system is modelled in WEC-Sim, a purpose-built WEC dynamics simulator. The PTO system is coupled to the open-source wave structure interaction solver NEMOH to calculate the average wave field η in the ‘near-field’. Using a WEC-specific novel PTO system model, the effect of a hydraulic PTO system on the WEC array power production and the near-field is compared to that of a linear PTO system. Results are given for a series of regular wave conditions for a single WEC and subsequently extended to a 5-WEC array. We demonstrate the quantitative and qualitative differences in the power and the ‘near-field’ effects between a 5-heaving cylindrical WEC array and a 5-OSWEC array. Furthermore, we show that modeling a hydraulic PTO system as a linear PTO system in the case of a heaving cylindrical WEC leads to considerable inaccuracies in the calculation of average absorbed power, but not in the near-field surface elevations. Yet, in the case of an OSWEC, a hydraulic PTO system cannot be reduced to a linear PTO coefficient without introducing substantial inaccuracies into both the array power output and the near-field effects. We discuss the implications of our results compared to previous research on WEC arrays which used simplified linear coefficients as a proxy for PTO systems.

Description: Smart grid (SG) vision has come to incorporate various communication technologies, which facilitate residential users to adopt different scheduling schemes in order to manage energy usage with reduced carbon emission. In this work, we have proposed a residential load management mechanism with the incorporation of energy resources (RESs) i.e., solar energy. For this purpose, a real-time electricity price (RTP), energy demand, user preferences and renewable energy parameters are taken as an inputs and genetic algorithm (GA) has been used to manage and schedule residential load with the objective of cost, user discomfort, and peak-to-average ratio (PAR) reduction. Initially, RTP is used to reduce the energy consumption cost. However, to minimize the cost along with reducing the peaks, a combined pricing model, i.e., RTP with inclining block rate (IBR) has been used which incorporates user preferences and RES to optimally schedule load demand. User comfort and cost reduction are contradictory objectives, and difficult to maximize, simultaneously. Considering this trade-off, a combined pricing scheme is modelled in such a way that users are given priority to achieve their objective as per their requirements. To validate and analyze the performance of the proposed algorithm, we first propose mathematical models of all utilized loads, and then multi-objective optimization problem has been formulated. Furthermore, analytical results regarding the objective function and the associated constraints have also been provided to validate simulation results. Simulation results demonstrate a significant reduction in the energy cost along with the achievement of both grid stability in terms of reduced peak and high comfort.

Description: To detect the categories and positions of various transformer components in inspection images automatically, this paper proposes a transformer component detection model with high detection accuracy, based on the structure of Faster R-CNN. In consideration of the significant difference in component sizes, double feature maps are used to adapt to the size change, by adjusting two weights dynamically according to the object size. Moreover, different from the detection of ordinary objects, there is abundant useful information contained in the relative positions between components. Thus, the relative position features are defined and introduced to the refinement of the detection results. Then, the training process and detection process are proposed specifically for the improved model. Finally, an experiment is given to compare the accuracy and efficiency of the improved model and the original Faster R-CNN, along with other object detection models. Results show that the improved model has an obvious advantage in accuracy, and the efficiency is significantly higher than that of manual detection, which suggests that the model is suitable for practical engineering applications.

Description: In recent years, concerns about severe environmental pollution and fossil fuel consumption has grabbed attention in the transportation industry, particularly in marine vessels. Another key challenge in ships is the fluctuations caused by high dynamic loads. In order to have a higher reliability in shipboard power systems, presently more generators are kept online operating much below their efficient point. Hence, to improve the fuel efficiency of shipboard power systems, the minimum generator operation with N-1 safety can be considered as a simple solution, a tradeoff between fuel economy and reliability. It is based on the fact that the fewer the number of generators that are brought online, the more load is on each generator such that allowing the generators to run on better fuel efficiency region. In all-electric ships, the propulsion and service loads are integrated to a common network in order to attain improved fuel consumption with lesser emissions in contrast to traditional approaches where propulsion and service loads are fed by separate generators. In order to make the shipboard power system more reliable, integration of energy storage system (ESS) is found out to be an effective solution. Energy storage devices, which are currently being used in several applications consist of batteries, ultra-capacitor, flywheel, and fuel cell. Among the batteries, lithium-ion is one of the most used type battery in fully electric zero-emission ferries with the shorter route (around 5 to 10 km). Hybrid energy storage systems (HESSs) are one of the solutions, which can be implemented in high power/energy density applications. In this case, two or more energy storage devices can be hybridized to achieve the benefits from both of them, although it is still a challenge to apply presently such application by a single energy storage device. The aim of this paper is to review several types of energy storage devices that have been extensively used to improve the reliability, fuel consumption, dynamic behavior, and other shortcomings for shipboard power systems. Besides, a summary is conducted to address most of the applied technologies mentioned in the literature with the aim of highlighting the challenges of integrating the ESS in the shipboard microgrids.

Description: The research of a general methodology to predict the pump performance in a reverse mode, knowing those of a pump in a direct mode, is a question that is still open. The scientific research is making many efforts toward answering this question, but at present, there is still not much clarity. This consideration has been the starting point of this research that thanks to artificial neural networks and evolutionary polynomial regression methods have tried to investigate and define the real weight of every input parameter, representing the efficiency of a pump in a direct way, on the output parameters, and representing efficiency of a pump used like a turbine.

Description: Groundwater heat pump systems (GWHPs) can achieve higher coefficient of performance (COP) than air-source heat pump systems by using the relatively stable temperature of groundwater. Among GWHPs, multi-well systems have lower initial investment costs than conventional closed-loop geothermal systems, because they typically require installation of fewer boreholes for the same building load. However, the performance of GWHPs depends significantly on the groundwater properties, such as groundwater temperature, permeability and water quality. Moreover, pumping and injecting of groundwater during long-term operation may lead to problems such as overflow or clogging of the wells. In order to ensure reliable energy from ground sources, the development of sustainable operation methods for multi-well systems is essential for preventing overflow and well clogging. In this study, we have developed a pairing technology that connects the injection and supply wells through a spillway. This pairing technology can be used to control groundwater levels in wells and can be sustainably operated. To accurately estimate the performance of a multi-well system with the proposed pairing technology, the heating and cooling performance of the developed system was compared to that of a standing column well (SCW) system in a field-scale experiment. Furthermore, the effects of the multi-well pairing system on groundwater levels in the injection well were analyzed by numerical simulation. Moreover, in order to decide the required conditions of the multi-well pairing system, case studies were conducted under various hydraulic conductivity and pumping conditions.

Description: This paper presents an Optimized Sensorless Charge Balance (OSCB) controller based on a damped current model for flyback converter operating in Discontinuous Conduction Mode (DCM). By solving total differential equations of non-ideal transformer currents, the damped current model is derived with consideration of parasitics, leakage inductance of transformer, and the Resistor-Capacitor-Diode (RCD) snubber circuit. Based on the proposed model, current observation and control algorithms of the Sensorless Charge Balance (SCB) controller are optimized, which forms the OSCB control strategy. The average current damping is considered in the equivalent discrete-time small signal model. Furthermore, frequency analyses show that OSCB controller achieves higher closed-loop bandwidth and lower overshoot than a SCB controller, which indicates an improved transient performance. Finally, both OSCB and conventional SCB controllers are experimentally evaluated on a flyback converter prototype.

Description: Hydraulic fracturing is an effective technology for enhancing the extraction of reservoir methane, as proved by field experience and laboratory experiments. However, unlike conventional reservoirs, coal seams had high stress sensitivity and high anisotropy. Therefore, the efficiency of hydraulic fracturing in coal seams needs to be investigated. In this study, hydraulic fracturing was performed at Nantong mine in the southeast Sichuan basin, China. The field investigation indicated that the hydraulic fracturing could significantly enhance the methane extraction rate of boreholes ten times higher than that of normal boreholes in one of the minable coal seams (named #5 coal seam). The performance of hydraulic fracturing in three districts revealed that compared with south flank, the fluid pressure was higher and the injection rate was lower in north flank. The methane extraction rate of south flank was inferior to that of north flank. It indicated hydraulic fracturing had less effect on #5 coal seam in south flank. Moreover, the injection of high-pressure water in coal seams could also drive methane away from boreholes. The methane extraction rate of the test boreholes demonstrated the existence of methane enrichment circles after hydraulic fracturing. It indicated that hydraulic fracturing did act on #5 coal seam in south flank. However, due to the high stress sensitivity of coal seams and the high geo-stress of south flank, the induced artificial fractures in #5 coal seam might close with the decline of the fluid pressure that led to a sharp decline of the methane extraction rate.

Description: This study describes a life cycle assessment (LCA) of a fourth generation (4G) nuclear power plant. A high temperature helium cooled reactor and gas turbine technology with modular helium reactor (GT-MHR) is used in this study as an example. This is currently one the safest design of a nuclear power plant. The study also takes into account impact of accidents and incidents (AI) which happened around the world at nuclear power generation facilities. The adopted method for the study is a hybrid LCA analysis. The analysis of each phase of the life cycle was done on the basis of process chain analysis (PCA). Where detailed data were not available, the Input/Output (I/O) databases was employed. The obtained results show that greenhouse gases (GHG) emissions and energy intensity per unit of electricity production are relatively low. In fact, these are even lower than emissions from a number of renewable energy sources. The results show considerably different greenhouse gases (GHG) emissions and energy intensity per unit of electricity production when effects of AI are taken into account.

Description: Heat exchanger designers need reliable thermal-hydraulic correlations to optimize heat exchanger designs. This work combines an adaptive sampling method with a Computational Fluid Dynamics (CFD) simulator to obtain increased accuracy and validity range of heat transfer and pressure drop predictions using a limited number of data points. Correlation efficacy was evaluated based on a steam generator case study. The sensitivity to the design parameters was analyzed in detail. The RMSE (root mean square error) of the developed correlations were reduced, through CFD sampling, from 28% to 15% for pressure drop, and from 33% to 25% heat transfer, compared to regression on experimental data only. The best reference correlations have RMSE values of 43% and 33% on pressure drop and heat transfer, respectively, on an independent validation set. Indeed, a radically different fin-tube geometry was suggested for the case study, compared to results using the Escoa correlations.The developed correlations show good to excellent agreement with trends in the CFD model. The quantitative error of predicted heat transfer and pressure drop coefficients at the case study optimum, however, was as large as those of the Escoa correlations. More data are likely needed to improve accuracy for compact heat exchanger designs further.

Description: Redox mediators could be used to improve the efficiency of microbial fuel cells (MFCs) by enhancing electron transfer rates and decreasing charge transfer resistance at electrodes. However, many artificial redox mediators are expensive and/or toxic. In this study, laccase enzyme was employed as a biocathode of MFCs in the presence of two natural redox mediators (syringaldehyde (Syr) and acetosyringone (As)), and for comparison, a commonly-used artificial mediator 2,2′-azinobis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) was used to investigate their influence on azo dye decolorization and power production. The redox properties of the mediator-laccase systems were studied by cyclic voltammetry. The presence of ABTS and As increased power density from 54.7 ± 3.5 mW m−2 (control) to 77.2 ± 4.2 mW m−2 and 62.5 ± 3.7 mW m−2 respectively. The power decreased to 23.2 ± 2.1 mW m−2 for laccase with Syr. The cathodic decolorization of Acid orange 7 (AO7) by laccase indicated a 12–16% increase in decolorization efficiency with addition of mediators; and the Laccase-Acetosyringone system was the fastest, with 94% of original dye (100 mgL−1) decolorized within 24 h. Electrochemical analysis to determine the redox properties of the mediators revealed that syringaldehyde did not produce any redox peaks, inferring that it was oxidized by laccase to other products, making it unavailable as a mediator, while acetosyringone and ABTS revealed two redox couples demonstrating the redox mediator properties of these compounds. Thus, acetosyringone served as an efficient natural redox mediator for laccase, aiding in increasing the rate of dye decolorization and power production in MFCs. Taken together, the results suggest that natural laccase redox mediators could have the potential to improve dye decolorization and power density in microbial fuel cells.

Description: Rotating wickless and stationary capillary cylindrical heat pipes are widely used heat transfer devices. Transient behavior of such heat pipes has been investigated numerically with computational fluid dynamics and lumped parameter models. In this paper, the advantages of both methods are combined into a novel engineering model that is low in computational cost but still accurate and rich in the details it provides. The model describes the interior dynamics of the heat pipe with a 2D representation of a cylindrical heat pipe. Liquid and vapor volumes are coarsely meshed in the axial direction. The cells are allowed to change in size in the radial direction during simulation. This allows for tracking the liquid/vapor interface without having to implement fine meshing. The model includes the equations for mass, momentum and energy and is applicable to both rotating and stationary heat pipes. The predictions of the model are validated with other experimental, numerical, and analytical works having an average deviation of less than 4%. The effects of various parameters on the system are explored. The presented model is suitable for the simulation of heat pipe systems in which both the level of detail and the computational cost are crucial factors.

Description: In this paper a numerical analysis of a T-joint fillet weld is performed to investigate the influences of different preheat temperatures and the interpass time on the longitudinal residual stress fields and structure deflections. In the frame of the numerical investigations, two thermo-mechanical finite element models, denoted M2 and M3, were analyzed and the results obtained were then compared with the model M1, where the preheating technique was not applied. It is concluded that by applying the preheat temperature prior to the start of welding the post-welding deformations of welded structures can be significantly reduced. The increase of the preheat temperature increased the longitudinal residual stress field at the ends of the plates. The influence of the interpass time between two weld passes on the longitudinal residual stress state and plate deflection was investigated on two preheated numerical models, M4 and M5, with an interpass time of 60 s and 120 s, respectively. The results obtained were then compared with the preheated model M3, where there was no time gap between the two weld passes. It can be concluded that with the increase of interpass time, the plate deflections significantly increase, while the influence of the interpass time on the longitudinal residual stress field can be neglected.

Description: This paper aims to contribute to developing a potential combined cycle air-breathing engine integrated into an aircraft design, capable of performing flight profiles on a commercial scale. This study specifically focuses on the single expansion ramp nozzle (SERN) and aircraft-engine integration with an emphasis on the combined cycle engine integration into the conceptual aircraft design. A parametric study using computational fluid dynamics (CFD) have been employed to analyze the sensitivity of the SERN’s performance parameters with changing geometry and operating conditions. The SERN adapted to the different operating conditions and was able to retain its performance throughout the altitude simulated. The expansion ramp shape, angle, exit area, and cowl shape influenced the thrust substantially. The internal nozzle expansion and expansion ramp had a significant effect on the lift and moment performance. An optimized SERN was assembled into a scramjet and was subject to various nozzle inflow conditions, to which combustion flow from twin strut injectors produced the best thrust performance. Side fence studies observed longer and diverging side fences to produce extra thrust compared to small and straight fences.

Description: Known as a multi-objective, large-scale, and complicated optimization problem, the multi-objective optimal power flow (MOOPF) problem tends to be introduced with many constraints. In this paper, compared with the frequently-used penalty function-based method (PFA), a novel constraint processing approach named the constraints-prior Pareto-domination approach (CPA) is proposed for ensuring non-violation of various inequality constraints on dependent variables by introducing the Pareto-domination principle based on the sum of constraint violations. Moreover, for solving the constrained MOOPF problem, the multi-objective firefly algorithm with CPA (MOFA-CPA) is proposed and some optimization strategies, such as the crowding distance calculation and non-dominated sorting based on the presented CPA, are utilized to sustain well-distributed Pareto front (PF). Finally, in order to demonstrate the feasible and effective improvement of MOFA-CPA, a comparison study between MOFA-CPA and MOFA-PFA is performed on two test systems, including three bi-objective optimization cases and three tri-objective optimization cases. The simulation results demonstrate the capability of the MOFA-CPA for obtaining PF with good distribution and superiority of the proposed CPA for dealing with inequality constraints on dependent variables. In addition, some quality indicators are used to evaluate the convergence, distribution, and uniformity of the PFs found by the MOFA-CPA and MOFA-PFA.

Description: Load forecasting is a key issue for efficient real-time energy management in smart grids. To control the load using demand side management accurately, load forecasting should be predicted in the short term. With the advent of advanced measuring infrastructure, it is possible to measure energy consumption at sampling rates up to every 5 min and analyze the load profile of small-scale energy groups, such as individual buildings. This paper presents applications of deep learning using feature decomposition for improving the accuracy of load forecasting. The load profile is decomposed into a weekly load profile and then decomposed into intrinsic mode functions by variational mode decomposition to capture periodic features. Then, a long short-term memory network model is trained by three-dimensional input data with three-step regularization. Finally, the prediction results of all intrinsic mode functions are combined with advanced measuring infrastructure measured in the previous steps to determine an aggregated output for load forecasting. The results are validated by applications to real-world data from smart buildings, and the performance of the proposed approach is assessed by comparing the predicted results with those of conventional methods, nonlinear autoregressive networks with exogenous inputs, and long short-term memory network-based feature decomposition.

Description: A novel step-up DC-DC converter with a three-winding-coupled-inductor which integrates a coupled-inductor and voltage-boost techniques for a distributed generation system is proposed in this paper. The two windings of the dotted terminal connection are charged by the input source; the proposed converter utilized smaller turn ratios, and can achieve higher gain when the active switch is turned on. The passive lossless clamped circuits not only can absorb the leakage energy, but also lower the switch voltage stresses; additionally, the reverse-recovery problem of diodes can be reduced to improve the system efficiency. Furthermore, the voltage stress of the output capacitor is reduced. The operating principle and corresponding theoretical analyses are discussed in detail. Finally, an experimental prototype with 50 kHz switching frequency, 40 V input voltage, 380 V output voltage and 400 W output power is set up to verify the validity of the proposed converter.

Description: The Real-Time Recurrent Learning Gradient (RTRL) algorithm is characterized by being an online learning method for training dynamic recurrent neural networks, which makes it ideal for working with non-linear control systems. For this reason, this paper presents the design of a novel Maximum Power Point Tracking (MPPT) controller with an artificial neural network type Adaptive Linear Neuron (ADALINE), with Finite Impulse Response (FIR) architecture, trained with the RTRL algorithm. With this same network architecture, the Least Mean Square (LMS) algorithm was developed to evaluate the results obtained with the RTRL controller and then make comparisons with the Perturb and Observe (P&O) algorithm. This control method receives as input signals the current and voltage of a photovoltaic module under sudden changes in operating conditions. Additionally, the efficiency of the controllers was appraised with a fuzzy controller and a Nonlinear Autoregressive Network with Exogenous Inputs (NARX) controller, which were developed in previous investigations. It was concluded that the RTRL controller with adaptive training has better results, a faster response, and fewer bifurcations due to sudden changes in the input signals, being the ideal control method for systems that require a real-time response.

Description: In this study, activated carbons (ACs) were produced from oil palm leaves (OPL) and palm kernel shells (PKS) using different concentrations (0%, 11%, and 33%) of H3PO4 as the activating agent. The Brunauer–Emmett–Teller (BET) results indicated that surface area decreases with the decreasing of the concentration of the H3PO4 in the following order: AC from oil palm leaves was (OPLAC-0% H3PO4) 〈 (OPLAC-11% H3PO4) 〈 (OPLAC-33% H3PO4), with the BET surface area values of 37, 760, and 780 m2/g, respectively. Similarly, the PKS-derived AC followed the same trend of (PKSAC-0% H3PO4) 〈 (PKSAC-11% H3PO4) 〈 (PKSAC-33% H3PO4), with the BET surface area values of 3, 52, and 1324 m2/g, respectively. Based on this finding, it was observed that H3PO4 had exhibited an influential role on enhancing the surface properties of the AC. On the contrary, it slightly decreased the graphitic trait of the AC by considering their IG/ID trends, which were generated from the Raman spectral analysis. The energy storage capacity of the AC was further tested using cyclic voltammetry. Three of the samples were found to have high capacitance values of 434 F g−1, 162 F g−1, and 147 F g−1 at 5 mVs−1. The first (434 F g−1) is much higher than the specific capacitance value (343 F g−1) of the only oil palm leaf-derived porous carbon nanoparticles ever reported in the literature.

Description: Nowadays climate change problems have been more and more concerns and urgent in the real world. Especially, the energy power consumption monitoring is a considerate trend having positive effects in decreasing affecting climate change. Non-Intrusive Load Monitoring (NILM) is the best economic solution to solve the electrical consumption monitoring issue. NILM captures the electrical signals from the aggregate energy consumption, feature extraction from these signals and then learning and predicting the switch ON/OFF of appliances used these feature extracted. This paper proposed a NILM framework including data acquisition, data feature extraction, and classification model. The main contribution is to develop a new transient signal in a different aspect. The proposed transient signal is extracted from the active power signal in the low-frequency sampling rate. This transient signal is used to detect the event of household appliances. In household appliances event detection, we applied to Decision Tree and Long Short-Time Memory (LSTM) models. The average accuracies of these models achieved 92.64% and 96.85%, respectively. The computational and result experiments present the solution effectiveness for the accurate transient signal extraction in the electrical input signals.

Description: The AM600 represents the conceptual design and layout of a Nuclear Power Plant Turbine Island intended to address challenges associated with emerging markets interested in nuclear power. When coupled with a medium sized nuclear reactor plant, the AM600 is designed with a unit capacity that aligns with constraints where grid interconnections and load flows are limiting. Through design simplification, the baseline turbine-generator shaftline employs a single low-pressure turbine cylinder, a design which to date has not been offered commercially at this capacity. Though the use of a ‘stiffer’ design, this configuration is intended to withstand, with a margin, the damage potential of torsional excitation from the grid-machine interface, specifically due to transient disturbances and negative sequence currents. To demonstrate the robust nature of the design, torsional rotordynamic analysis is performed for the prototype shaftline using three dimensional finite element modelling with ANSYS® software. The intent is to demonstrate large separation of the shaftline natural frequencies from the dominant frequencies for excitation. The analysis examined both welded drum and monoblock type Low Pressure Turbine rotors for single cylinder and double cylinder configurations. For each, the first seven (7) torsional natural frequencies (ranging from zero–190 Hz) were extracted and evaluated against the frequency exclusion range (i.e., avoidance of 1× and 2× grid frequency). Results indicate that the prototype design of AM600 shaftline has adequate separation from the dominant excitation frequencies. For verification of the ANSYS® modelling of the shaftline, a simplified lumped mass calculation of the natural frequencies was performed with results matching the finite element analysis values.

Description: With the increasing participation of wind generation in the power system, a wind power plant (WPP) with an energy storage system (ESS) has become one of the options available for a black-start power source. In this article, a method for the energy storage configuration used for black-start is proposed. First, the energy storage capacity for starting a single turbine was determined. Then, a hierarchical planning model was established. This model did not consider the starting efficiency of the WPP, but it did consider the layout of the energy storage in the WPP and the balance of the terminal voltage when starting the WPP. Finally, the feasibility and value of the proposed method and model were verified in a 49.5 MW WPP with an ESS (a power rating of 2.24 MW and energy capacity of about 1.68 MWh). The result suggests that configuring an ESS with a small capacity on the side of the turbine can achieve black-start for a WPP with an ESS as the power source.

Description: To control multiple series units of distributed power flow controller (DPFC), a hierarchical control method is proposed. This coordination control system consists of a coordination controller and multiple series unit controllers. According to the demand of power flow ordered by a dispatch center, the corresponding series-compensated voltage is calculated by a high-level controller and transferred to each series unit controller. Comparing the targeted compensated voltage with actual injected voltage, the modulation signal of the converter will be modified to change the power flow accurately. The DPFC system model is built in Power Systems Computer Aided Design/ Electromagnetic Transients including DC (PSCAD/EMTDC). The simulation result indicates that the proposed hierarchical control method is effective and can be considered as an option for practical engineering applications in the future.

Description: With the continuous development of the social economy, residents living in rural China pay more attention to the heating quality and require a comfortable and healthy indoor thermal environment in winter. The existing traditional heating methods cannot meet the high-quality heating demands. Although the new heating methods based on clean energy can satisfy the needs of residents in terms of energy saving, environmental protection and thermal comfort, they have not been widely used due to their high initial investment, the misunderstanding of principal functions and the perceived difficulty of application. This study firstly summarizes various available heating methods for rural areas from aspects of technical characteristics, environmental friendliness, indoor comfort, and economy. Then it gives advice for government and relevant institutions to increase publicity for new heating methods. It aims to provide a theoretical basis and feasible suggestions for the selection of heating methods for rural residents in China. It also aims to provide theoretical policy making references for the transformation of the original rural heating methods.

Description: The purpose of this paper is the performance investigation of a Permanent Magnet Synchronous Generator (PMSG) system, suitable for wind power applications and the comparison of the machine electromagnetic characteristics under open and closed control loop implementations. The copper and iron losses are estimated and compared for the above control systems with the use of the Steinmetz-Bertotti loss separation equation. In addition, the effect of the rotating magnetic field on the total losses is studied. The generator is simulated using Finite Element Analysis (FEA), while the rest of the components are connected to the machine model using a drawing window of the FEA software and suitable command files. The close loop control used in the present study results to less losses and greater machine efficiency. The main novelty of the paper is the simulation of the PMSG coupled with a converter and control schemes using FEA, which ensures more accurate results of the whole system and allows the detailed machine electromagnetic study, while the majority of existing papers on this topic uses simulation tools that usually simulate in detail the electric circuits but not the machine. The FEM model is validated by experimental results.

Description: Cut solar cells have received considerable attention recently as they can reduce electrical output degradation when the c-Si solar cells (crystalline-silicon solar cells) are shaded. Cut c-Si solar cells have a lower short-circuit current than normal solar cells and the decrease in short-circuit currents is similar to the shading effect of c-Si solar cells. However, the results of this study’s experiment show that the shadow effect of a c-Si solar cell reduces the V o c (open circuit voltage) in the c-Si solar cell but the V o c does not change when the c-Si solar cell is cut because the amount of incident light does not change. In this paper, the limitations of the electrical power analysis of the cut solar cells were identified when only photo current was considered and the analysis of the electric output of the cut c-Si solar cells was interpreted with a method different from that used in previous analyses. Electrical output was measured when the shaded and cut rates of c-Si solar cells were increased from 0% to 25, 50 and 75%, and a new theoretical model was compared with the experimental results using MATLAB.

Description: In order to enhance the spreading of renewable energy sources in the Italian electric power market, as well as to promote self-production and to decrease the phase delay between energy production and consumption, energy storage solutions are catching on. Nowadays, in general, small size electric storage batteries represent a quite diffuse technology, while air liquid-compressed energy storage solutions are used for high size. The goal of this paper is the development of a numerical model for small size storage, environmentally sustainable, to exploit the higher efficiency of the liquid pumping to compress air. Two different solutions were analyzed, to improve the system efficiency and to exploit the heat produced by the compression phase of the gas. The study was performed with a numerical model implemented in Matlab, by analyzing the variation of thermodynamical parameters during the compression and the expansion phases, making an energetic assessment for the whole system. The results show a good global efficiency, thus making the system competitive with the smallest size storage batteries.

Description: With the development of urbanization, people’s living standards have improved. Simultaneously, the growing aggravation of resource shortages and environmental pollution have also gradually attracted widespread attention. Low-carbon energy planning can effectively reduce dependence on fossil resources and carbon emissions to the atmosphere, as well as improve the utilization of resources. Therefore, the formulation and evaluation of low-carbon energy planning have become the focus of attention for related colleges and institutions. This paper puts forward a hybrid multi-criteria decision making(MCDM) method combining decision making trial and evaluation laboratory(DEMATEL), analytical network process(ANP), and VIKOR to obtain the weight of each criterion and evaluate each alternative about low-carbon energy planning for building. A hierarchy structure of criteria involving cost, safety, reliability, and environment protection is built. Afterwards, a case of four alternatives is applied for testifying this methodology. Lastly, a comparison with prior methodologies serves as proof of the raised ranking. The presentation has proved that this methodology offers a more precise and effective foundation for decisions about low-carbon energy planning evaluation.

Description: Due to the vulnerability and high risk of the ship environment, the Ship Information System (SIS) should provide 24 hours of uninterrupted protection against network attacks. Therefore, the corresponding intrusion detection mechanism is proposed for this situation. Based on the collaborative control structure of SIS, this paper proposes an anomaly detection pattern based on risk data analysis. An intrusion detection method based on the critical state is proposed, and the corresponding analysis algorithm is given. In the Industrial State Modeling Language (ISML), risk data are determined by all relevant data, even in different subsystems. In order to verify the attack recognition effect of the intrusion detection mechanism, this paper takes the course/roll collaborative control task as an example to carry out simulation verification of the effectiveness of the intrusion detection mechanism.