ALBERT

Description: This paper proposes an equivalent circuit model to obtain the transient electrical stress quantitatively in medium voltage medium frequency transformers in modern power electronics. To verify this model, transient simulation is performed on a 1.5 kV/1 kHz transformer, revealing voltage overshoot quantitatively between turns and layers of the transformer’s HV winding. Effects of rise time of the input pulse voltage, stray capacitance of the winding insulation, and their interactions on the voltage overshot magnitude are presented. With these results, we propose limiting the voltage overshoot and, thereafter, enhancing medium voltage medium frequency transformer’s insulation capability, which throws light on the transformer’s insulation design. Additionally, guidance on the future studies on aging and endurance lifetime of the medium voltage medium frequency transformer’s insulation could be given.

Description: Developments in the design of wind turbines with augmentation are advancing around the globe with the goal of generating electricity close to the user in built-up areas. This is certain to help lessen the power generation load as well as distribution and transmission network costs by reducing the distance between the user and the power source. The main objectives driving the development and advancement of vertical-axis wind turbines are increasing the power coefficient and the torque coefficient by optimizing the upstream wind striking on the rotor blades. Unlike horizontal-axis wind turbines, vertical axis turbines generate not only positive torque but also negative torque during operation. The negative torque generated by the returning blade is a key issue for vertical-axis wind turbines (VAWTs) that is counterproductive. Installation of wind deflectors for flow augmentation helps to reduce the negative torque generated by the returning blades as well as enhance the positive torque by creating a diversion in the upstream wind towards the forwarding blade during operation. This paper reviews various designs, experiments, and CFD simulations of wind deflectors reported to date. Optimization techniques for VAWTs incorporating wind deflectors are discussed in detail. The main focus of the review was on the installation position and orientation of the deflectors and their potential contribution to increasing the power coefficient. Topics for future study are suggested in the conclusion section of the paper.

Description: This empirical study assesses the effect of CO2 emissions, urbanization, energy consumption, and agriculture on Thailand’s economic growth using a dataset between 1970 and 2018. The ARDL and the frequency domain causality (FDC) approaches were applied to assess these interconnections. The outcome of the bounds test suggested a long-term association among the variables of investigation. The ARDL outcomes reveal that urbanization, agriculture, energy consumption, and CO2 emissions positively trigger Thailand’s economic growth. Additionally, the frequency domain causality test was used to detect a causal connection between the series. The main benefit of this technique is that it can detect a causal connection between series at different frequencies. To the understanding of the authors, this is the first study in the case of Thailand that will apply the FDC approach to capture the causal linkage between GDP and the regressors. The outcomes of the causality test suggested that CO2 emissions, urbanization, energy consumption, and agriculture can predict Thailand’s economic growth in the long term. These outcomes have far-reaching implications for economic performance and Thailand’s macroeconomic indicators.

Description: Flow-induced vibration is a canonical issue in various engineering fields, leading to fatigue or immediate damage to structures. This paper numerically investigates flow-induced vibrations of a cylinder interacting with the wake of another cylinder at a Reynolds number Re = 150. It sheds light on the effects of mass ratio m*, damping ratio, and mass-damping ratio m*ζ on vibration amplitude ratio A/D at different reduced velocities Ur and cylinder spacing ratios L/D = 1.5 and 3.0. A couple of interesting observations are made. The m* has a greater influence on A/D than ζ although both m* and ζ cause reductions in A/D. The m* effect on A/D is strong for m* = 2–16 but weak for m* 〉 16. As opposed to a single isolated cylinder case, the mass-damping m*ζ is not found to be a unique parameter for a cylinder oscillating in a wake. The vortices in the wake decay rapidly at small ζ. Alternate reattachment of the gap shear layers on the wake cylinder fuels the vibration of the wake cylinder for L/D = 1.5 while the impingement and switch of the gap vortices do the same for L/D = 3.0.

Description: This comparative study inspects the heat transfer characteristics of magnetohydrodynamic (MHD) nanofluid flow. The model employed is a two-phase fluid flow model. Water is utilized as the base fluid, and zinc and titanium oxide (Zn and TiO2) are used as two different types of nanoparticles. The rotation of nanofluid is considered along the z-axis, with velocity ω*. A similarity transformation is used to transform the leading structure of partial differential equations to ordinary differential equations. By using a powerful mathematical BVP-4C technique, numerical results are obtained. This study aims to describe the possessions of different constraints on temperature and velocity for rotating nanofluid with a magnetic effect. The outcomes for the rotating nanofluid flow and heat transference properties for both types of nanoparticles are highlighted with the help of graphs and tables. The impact of physical concentrations such as heat transference rates and coefficients of skin friction are examined. It is noted that rotation increases the heat flux and decreases skin friction. In this comparative study, Zn-water nanofluid was demonstrated to be a worthy heat transporter as compared to TiO2-water nanofluid.

Description: This article discusses the problems of exhaust gas emissions in the context of the possibility of their reduction through the use of fuels with hydrogen as an additive or hydrotreatment. These fuels, thanks to their properties, may be a suitable response to more and more demanding restrictions on exhaust emissions. The use of such fuels in reactivity controlled dual fuel engines (RCCI) is currently the most effective way of using them in internal combustion (IC) engines. Low-temperature combustion in this type of engine allows the use of all modern fuels intended for combustion engines with high thermal efficiency. Thermal efficiency higher than in classic engines allows for additional reduction of CO2 emissions. In this work, the research on this subject was compiled, and conclusions were drawn as to further possibilities of popularizing the use of these fuels in a wide spectrum of applications and the prospect of using them on a mass scale.

Description: According to star graph and winding distribution, winding MMFs of three kinds of 12-slot/10-pole multi-phase and multi-layer winding layout are analyzed by the improved winding function method. Analysis results show that multi-phase and multi-layer winding can suppress even order and (12n ± 1) order harmonics, thereby reducing the eddy-current loss in PMs. Based on the unfolded LPMSM model, rotor MMF, air gap flux density, and no-load back-EMF are analyzed by the analytical permeance function method, which is validated by Teslameter and no-load experiment. Winding MMF is validated by FEM. An axial-flux integrated starting/generator (ISG) with double-three-phase four-layer (DTP-FL) winding, segmented armature and PM, and centrifugal fan is designed and manufactured. The no-load and load test with two groups of resistance established has validated the reasonability of the mentioned method. Experiments show that the axial-flux ISG prototype can run at a relative temperature rise.

Description: The free-piston Stirling engine is a closed-cycle regenerative heat engine that converts heat energy into mechanical work, and requires a spring element for vibratory operations of the displacer and power pistons. In this study, the geometry of the flexural spring design was optimized through structural finite element analyses and fatigue test evaluations. First, we constructed a target design space considering the required natural frequency of the displacer spring assembly under the geometric constraints of total mass and module height. The design of experiments was employed to construct simulation cases for design factors such as the outer diameter, thickness, and number of spirals in the spring sheet. As a result, the optimized design values were obtained to satisfy the design requirements. We also fabricated a test spring specimen and conducted fatigue tests using a linear actuator system developed to have the same motion as the engine. The test results indicated that the optimized spiral spring had no fracture under operating conditions with the design piston amplitude, revealing the effectiveness of the design method.

Description: Lead-acid batteries utilised in electrical substations release hydrogen and oxygen when these are charged. These gases could be dangerous and cause a risk of fire if they are not properly ventilated. Therefore, this research seeks to design and implement a network control panel for heating, ventilation, and air conditioning system (HVACS). This is achieved by using a specific range of controllers, which have more than thirty loops of proportional, integral, and derivative (PID) control to achieve a cost-effective design. It performs the required function of extracting hydrogen and oxygen, maintaining the desired temperature of the battery storage room within recommended limits (i.e., 25 ± 1 °C tolerance) without compromising quality, as set out in the user requirement specification. The system control panel allows the user to access control parameters such as changing temperature set-points, fan-speed, sensor database, etc. It does this automatically and allows no human interface after all necessary settings and installation are completed. The hardware is configured to detect extreme hydrogen and oxygen gas content in the battery room and to ensure that the HVACS extracts the gas content to the outside environment. The system’s results show that the network control panel operates effectively as per the recommended system requirements. Therefore, the effective operation of the HVACS ensures sufficient gas ventilation, thus mitigating the risk of fire in a typical battery storage room. Furthermore, this also enhances battery lifespan because of regulated operating temperature, which is conducive to minimise the effect of sulfation in lead–acid batteries (LAB). The extraction of toxic gases, regulation of temperature, ensuring suitable humidity in UPS battery room is important as it provides longer operational service of equipment, thus reducing frequent maintenance in these rooms. This benefits the electricity supply industry and helps in saving for unplanned maintenance costs.

Description: Nuclear and renewables energies are the two variants for low-carbon energy and the evolving grid suggests possible synergies between them. Nuclear energy introduces supple operations based on power demand, while renewables such as PV and wind hybrid systems depend on the presence and strength of sunlight or wind. For grid stability, there is need to improve their performance in order to overcome the impact of this disadvantage. The paper is a step in this direction as it addresses a detailed comprehensive dynamic modeling and an efficient control of grid-connected energy sources such as PV or wind system to increase system reliability and to ensure the power quality and safe operation of critical demands. The behavior of the suggested hybrid system is tested at different climate circumstances such as variation of sun radiation and wind speed. The PV is equipped with a boost converter and a three-phase pulse width modulation (PWM) inverter. The wind energy comprises a doubly fed generator (DFIG) based on a variable-speed wind turbine. The two controllers’ rotor-side and grid-side converters of DFIG have the ability to generate and observe reactive power, to keep constant speed of the rotor and control the DC-link voltage. The proposed scheme was investigated using MATLAB software. The maximum power point tracking (MPPT) was used for two systems, PV and wind, in varying weather conditions. The simulation results prove that the voltage at the point of common coupling was constant. Furthermore, the injected current of the grid side was in sinusoidal form and was synchronized with grid side voltage. In addition, the injected power-to-utility grid was around power delivered by the hybrid PV and wind system.

Description: The optimal expansion of AC medium-voltage distribution grids for rural applications is addressed in this study from a heuristic perspective. The optimal routes of a distribution feeder are selected by applying the concept of a minimum spanning tree by limiting the number of branches that are connected to a substation (mixed-integer linear programming formulation). In order to choose the caliber of the conductors for the selected feeder routes, the maximum expected current that is absorbed by the loads is calculated, thereby defining the minimum thermal bound of the conductor caliber. With the topology and the initial selection of the conductors, a tabu search algorithm (TSA) is implemented to refine the solution with the help of a three-phase power flow simulation in MATLAB for three different load conditions, i.e., maximum, medium, and minimum consumption with values of 100%, 60%, and 30%, respectively. This helps in calculating the annual costs of the energy losses that will be summed with the investment cost in conductors for determining the final costs of the planning project. Numerical simulations in two test feeders comprising 9 and 25 nodes with one substation show the effectiveness of the proposed methodology regarding the final grid planning cost; in addition, the heuristic selection of the calibers using the minimum expected current absorbed by the loads provides at least 70% of the calibers that are contained in the final solution of the problem. This demonstrates the importance of using adequate starting points to potentiate metaheuristic optimizers such as the TSA.

Description: In a nuclear power plant environment, low-voltage cables experience different stresses during their service life which challenge their integrity. A non-destructive and reliable condition monitoring technique is desired to determine the state of these low-voltage cables during service and for the life extension of nuclear power plants. Hence, in this research work, an EPR/CSPE-based low-voltage cable was exposed to γ-rays for five different absorbed doses. The overall behavior of the cable under stress was characterized by frequency and time domain electrical measurements (capacitance, tan δ, and Extended Voltage Response) and a mechanical measurement (elongation at break). Significant variations in the electrical parameters were observed, as was a decline in the elongation at break values. A strong correlation between the measurement methods was observed, showing the ability of the electrical methods to be adopted as a non-destructive condition monitoring technique.

Description: In this paper, the effect of heat injection on productivity of Fuyu oil shale during in-situ pyrolysis was studied by using heat flow coupling analysis method. It is found that fluid conducts heat transmission to the oil shale stratum mainly along the fissure formed by hydraulic fracturing. With the increase of heating time, the oil shale on both sides of fissures were effectively pyrolyzed, and the porosity of the formation increases and the diffusion range of the nitrogen to the oil shale stratum is also improved. After 200 days, the oil shale around the fractures first reaches the pyrolysis temperature, and 700 days later, the average temperature of the oil shale stratum reaches 500 °C; therefore, the whole oil shale can be effectively pyrolyzed. Productivity analysis shows that the best exploitation temperature is 500 °C. When the gas injection rate is in the range of 1.0~11.0 m3/min, different degrees of heat loss will occur, and the output is also different. The pyrolysis time reaches 100~150 days, showing the peak value of daily production, which is between 0.5~3.2 m3/day. The pressure of displacement fluid affects oil shale product recovery in in-situ pyrolysis. High pressure helps to improve the displacement efficiency of oil and gas products and increase the productivity of oil shale in-situ pyrolysis. The best acting pressure is 9.5 MPa.

Description: The electricity sector aims to achieve a balanced progress in all three dimensions of the energy trilemma: affordability, decarbonisation and security of supply. Separate strategies for decarbonisation and security of supply have been pursued; each with close attention to minimising costs, thus consistent with the affordability aspect of the trilemma. However, while it is evident that the pathway for decarbonisation increases pressure on security of supply, the pressures that cost-minimising security of supply measures are putting on decarbonisation goes unaddressed. The United Kingdom (UK) is a global leader in the transition towards a decarbonised economy and aims to achieve net-zero emissions by 2050. As a major part of the UK, Great Britain (GB) has achieved greater than 50% of low-carbon electricity generation and the grid’s carbon intensity has dropped by 36% over the period 2015–2019. However, balancing services that provide security of supply uses only 8% of low-carbon generation. Their carbon intensity is double the grid’s average and this gap is widening. This is an effect of a systemic reliance on carbon-intensive fuels. Financial support for capital investment for flexible low-carbon technologies is much needed. The GB context suggests that an integrated strategy covering all three dimensions of the trilemma might achieve an improved balance between them and unlock an affordable, net-zero emissions and secure power system.

Description: Deep learning has recently emerged as a successful approach to produce accurate subgrid-scale (SGS) models for Large Eddy Simulations (LES) in combustion. However, the ability of these models to generalize to configurations far from their training distribution is still mainly unexplored, thus impeding their application to practical configurations. In this work, a convolutional neural network (CNN) model for the progress-variable SGS variance field is trained on a canonical premixed turbulent flame and evaluated a priori on a significantly more complex slot burner jet flame. Despite the extensive differences between the two configurations, the CNN generalizes well and outperforms existing algebraic models. Conditions for this successful generalization are discussed, including the effect of the filter size and flame–turbulence interaction parameters. The CNN is then integrated into an analytical reaction rate closure relying on a single-step chemical source term formulation and a presumed beta PDF (probability density function) approach. The proposed closure is able to accurately recover filtered reaction rate values on both training and generalization flames.

Description: Accurately forecasting the output of grid connected wind and solar systems is critical to increasing the overall penetration of renewables on the electrical network. This includes not only forecasting the expected level, but also putting error bounds on the forecast. The National Electricity Market (NEM) in Australia operates on a five minute basis. We used statistical forecasting tools to generate forecasts with prediction intervals, trialing them on one wind and one solar farm. In classical time series forecasting, construction of prediction intervals is rudimentary if the error variance is constant—termed homoscedastic. However, if the variance changes—either conditionally as with wind farms, or systematically because of diurnal effects as with solar farms—the task is much more complicated. The tools were trained on segments of historical data and then tested on data not used in the training. Results from the testing set showed good performance using metrics, including Coverage and Interval Score. The methods used can be adapted to various time scales for short term forecasting.

Description: One of the key challenges of developing countries is to tackle the mitigation of the impacts of rapid and uncontrolled urbanization. Assessing this phenomenon is crucial to lessen the consequences for the environment and society. ‘Literature has been concentrated in planning strategies for the cities’ adaptation and engagements to the principles of green development ensuring a long-term quality of life for their citizens. Hereby, smart technologies and applications consist of two of the most encouraging concepts for solutions for achieving the 2030 and 2050 horizon targets towards clean energy transition and carbon neutrality. In academia, scholars have already raised the importance of ‘smartness’ to define the adaptative patterns for the global pressures of climate change and uncontrolled urban growth. The mitigation of these phenomena is crucial to ensure the cities’ future and lessen their impacts. This study seeks a strategic and smart-driven vision to leverage smartness on the phenomenon of rapid urbanization that occurred in the case of Beijing, China. Defining and evaluating the environmental impacts in line with the RIAM approach as one of its main targets. Future works can be focused on addressing solutions in similar cases in further developing countries to not only overcome environmental, but also economic, social, and digital complications.

Description: The objective of this paper is to evaluate the contribution of energy storage systems to resource adequacy of power systems experiencing increased levels of renewables penetration. To this end, a coherent methodology for the assessment of system capacity adequacy and the calculation of energy storage capacity value is presented, utilizing the Monte Carlo technique. The main focus is on short-duration storage, mainly battery energy storage systems (BESS), whose capacity values are determined for different power and energy configurations. Alternative operating policies (OPs) are implemented, prioritizing system cost or reliability, to demonstrate the significant effect storage management may have on its contribution to system adequacy. A medium-sized island system is used as a study case, applying a mixed integer linear programming (MILP) generation scheduling model to simulate BESS and system operation under each OP, in order to determine capacity contribution and overall performance in terms of renewable energy sources (RES) penetration, system operating cost and BESS lifetime expectancy. This study reveals that BESS contribution to system adequacy can be significant (capacity credit values up to ~85%), with energy capacity proving to be the most significant parameter. Energy storage may at the same time enhance system reliability, reduce generation cost and support RES integration, provided that it is appropriately managed; a combined reliability-oriented and cost-driven management approach is shown to yield optimal results.

Description: This research proposes a generic smart cloud-based system in order to accommodate multiple scenarios where agriculture farms using Internet of Things (IoTs) need to be monitored remotely. The real-time and stored data are analyzed by specialists and farmers. The cloud acts as a central digital data store where information is collected from diverse sources in huge volumes and variety, such as audio, video, image, text, and digital maps. Artificial Intelligence (AI) based machine learning models such as Support Vector Machine (SVM), which is one of many classification types, are used to accurately classify the data. The classified data are assigned to the virtual machines where these data are processed and finally available to the end-users via underlying datacenters. This processed form of digital information is then used by the farmers to improve their farming skills and to update them as pre-disaster recovery for smart agri-food. Furthermore, it will provide general and specific information about international markets relating to their crops. This proposed system discovers the feasibility of the developed digital agri-farm using IoT-based cloud and provides solutions to problems. Overall, the approach works well and achieved performance efficiency in terms of execution time by 14%, throughput time by 5%, overhead time by 9%, and energy efficiency by 13.2% in the presence of competing smart farming baselines.

Description: The article presents the results of preliminary research aimed at determining the possibility of using microencapsulated phase change material (mPCM) slurries as a working fluid in installations with a flat liquid solar collector. In the tests, the following were used as the working fluid: water (reference liquid) and 10% wt. and 20% wt. of an aqueous solution of the product under the trade name MICRONAL® 5428 X. As the product contained 43% mPCM, the mass fraction of mPCM in the working liquid was 4.3% and 8.6%, respectively. The research was carried out in laboratory conditions in the range of irradiance I = 250–950 W/m2. Each of the three working fluids flowed through the collector in the amount of 20 kg/h, 40 kg/h, and 80 kg/h. The working fluid was supplied to the collector with a constant temperature Tin = 20 ± 0.5 °C. It was found that the temperature of the working fluid at the collector outlet increases with the increase in the radiation intensity, but the temperature achieved depended on the type of working fluid. The greater the share of mPCM in the working liquid, the lower the temperature of the liquid leaving the solar collector. It was found that the type of working fluid does not influence the achieved thermal power of the collector. The negative influence of mPCM on the operation of the solar collector was not noticed; the positive aspect of using mPCM in the solar installation should be emphasized—the reduced temperature of the medium allows the reduction in heat losses to the environment from the installation, especially in a low-temperature environment.

Description: Thermodynamic analysis of a gasification process was conducted assuming that it is composed of two successive stages, namely: pyrolysis reaction followed by a stage of gasification reaction. This approach allows formulation the models of selected gasification processes dominating in industrial applications namely: Shell (coal), SES (coal), and DFB (dual fluid bed, biomass) gasification. It was shown that the enthalpy of fuel formation is essential for the correctness of computed results. The specific computational formula for a wide range of fuels enthalpy of formation was developed. The following categories were evaluated in terms of energy balance: total reaction enthalpy of gasification process, enthalpy of pyrolysis reaction, enthalpy of gasification reaction, heat demand for pyrolysis reaction, and heat demand for gasification reactions. The discussion of heat demand for particular stages of gasification related to the various processes was performed concluding the importance of the pyrolysis stage.

Description: Understanding the amount of energy a tire is subjected to is one of the key elements to perform in motorsport competitions, especially in Formula 1 feeder categories, where the number of tires is limited over the race weekend to contain costs. This forces teams to use worn tires towards the end of the event. Therefore, tires are usually chosen only relying on their external shape or based on the kilometers traveled. Moreover, being aware of how a setup change impacts tires can be a breakthrough in tire management, especially in tracks where tire wear is limiting the overall performance. This paper provides a scientific method aimed at helping race engineers in tire management to maintain a high performance level through the entire race weekend.

Description: The objectives of this work are: (a) to present a new system for building heating which is based on underground energy storage, (b) to develop a mathematical model of the system, and (c) to optimise the energy performance of the system. The system includes Photovoltaic Thermal Hybrid Solar Panels (PVT) panels with cooling, an evacuated solar collector and a water-to-water heat pump. Additionally, storage tanks, placed underground, are used to store the waste heat from PVT panels cooling. The thermal energy produced by the solar collectors is used for both domestic hot water preparation and thermal energy storage. Both PVT panels and solar collectors are assembled with a sun-tracking system to achieve the highest possible solar energy gain. Optimisation of the proposed system is considered to achieve the highest Renewable Energy Sources (RES) share during the heating period. Because the resulting optimisation problem is nonlinear, the classical gradient-based optimisation algorithm gives solutions that are not satisfying. As alternatives, three heuristic global optimisation methods are considered: the Genetic Algorithm (GA), the Particle Swarm Optimisation (PSO) algorithm, and the Jaya algorithm. It is shown that the Jaya algorithm outperforms the GA and PSO methods. The most significant result is that 93% of thermal energy is covered by using the underground energy storage unit consisting of two tanks.

Description: Optimizing the operating speed curve of trains without adding new energy storage facilities is essential in the energy-saving operation of railways. In this paper, we propose an optimal train speed curve planning method for driving trains more energy efficiently. A refined traction energy evaluation model for induction motor propulsion systems is first presented. The proposed model considers the efficiency of the traction motor at different operating points and the efficiency of the inverter and gearbox. Then, the optimal energy-efficient speed profile problem is transformed into a multistep decision problem and solved using dynamic programming (DP). To verify the effectiveness of the proposed method, a case study was conducted on an actual subway line. The results obtained indicate that the speed curve produced by the proposed method results in a 20% energy consumption saving compared with the speed curve for actual operations. Furthermore, the results of comparison with a genetic algorithm indicate that the DP algorithm is better able to satisfy the constraints of the train traction system. Solving the optimal speed curve using the proposed method and programming the onboard controller of the train according to the optimal speed curve enables the train to be driven with greater energy efficiency.

Description: Knowledge of lightning impulse (LI) voltage distribution over transformer windings during the design stage of the transformer is very important. Specific design differences in inductive voltage transformers make the transient analysis approach different to the approach to the power transformers. In this paper, a methodology for acquiring lightning impulse voltage distribution over high-voltage (HV) winding of inductive voltage transformers is presented and evaluated. Resistance, inductance, and capacitance matrices are calculated using the integral and boundary element methods (BEM) approach. Additionally, in order to improve the capacitance matrix solver, adaptive cross approximation (ACA) is applied. These parameters are then used to solve the equivalent circuit model in time domain. In order to evaluate the methodology, an experimental and numerical investigation of the layer discretisation, iron core influence, and accuracy of the proposed methodology is performed. The comparison of numerical results with measurements confirms the validity of the methodology.

Description: The viability of Variable Renewable Energy (VRE)-investment strategies depends on the response of dispatchable producers to satisfy the net load. We lack a simple research tool with sufficient complexity to represent major phenomena associated with the response of dispatchable producers to the integration of high shares of VRE and their impact on system costs. We develop a minimization of the system cost allowing one to quantify and decompose the system value of VRE depending on an aggregate dispatchable production. Defining the variable cost of the dispatchable generation as quadratic with a coefficient depending on macroeconomic factors such as the cost of greenhouse gas emissions leads to the simplest version of the model. In the absence of curtailment, and for particular parameter values, this version is equivalent to a mean-variance problem. We apply this model to France with solar and wind capacities distributed over the administrative regions of metropolitan France. In this case, ignoring the wholesale price effect and variability has a relatively small impact on optimal investments, but leads to largely underestimating the system total cost and overestimating the system marginal cost.

Description: The use of energy in buildings is at the crossroads between comfort and productivity requirements, passive and active technological options, and health and environmental consequences [...]

Description: Considering the influence of user equipment voltage tolerance characteristics and sag types on the evaluation results, this paper proposes a voltage sag severity evaluation method for the system side which considers the influence of the voltage tolerance curve and sag type. As such, a quantitative evaluation of the severity of voltage sag events can be achieved. Firstly, the user’s voltage tolerance curve is used to construct the comparison reference value of the energy index, in order to realize the rapid analysis of the severity of the sag event in the normal area and the abnormal area. Secondly, aiming at the problem of insufficient descriptions of the severity difference of sag events in uncertain areas, an improved energy index evaluation model combined with user tolerance characteristics is established through an interval division and interval weight calculation, so as to divide and evaluate the severity of sag events in uncertain areas. Considering the influence of the sag type on the voltage tolerance curve and user equipment, the energy index correction factor is then constructed, and the measurement function is used for an interval evaluation to obtain the ranking result of the voltage sag severity, which is more in line with the actual situation. Finally, the rationality and effectiveness of the proposed method are verified by analyzing 24 voltage sag events at a monitoring node.

Description: This study investigates the input–output energy-flow patterns and CO2 emissions from the wheat–rice crop rotation system. In this regard, an arid region of Punjab, Pakistan was selected as the study area, comprising 4150 km2. Farmers were interviewed to collect data and information on input/output sources during the 2020 work season. The total energy from these sources was calculated using appropriate energy equivalents. Three energy indices, including energy use efficiency (ηe), energy productivity (ηp), and net energy (ρ), were defined and calculated to investigate overall energy efficiency. Moreover, the data envelopment analysis (DEA) technique was used to optimize the input energy in wheat and rice production. Finally, CO2 emissions was calculated using emissions equivalents from peer-reviewed published literature. Results showed that the average total energy consumption in rice production was twice the energy consumed in wheat production. However, the values of ηe, ηp, and ρ were higher in wheat production and calculated as 5.68, 202.3 kg/GJ, and 100.12 GJ/ha, respectively. The DEA showed the highest reduction potential in machinery energy for both crops, calculated as −42.97% in rice production and −17.48% in wheat production. The highest CO2 emissions were found in rice production and calculated as 1762.5 kg-CO2/ha. Our conclusion indicates that energy consumption and CO2 emissions from wheat–rice cropping systems can be minimized using optimized energy inputs.

Description: The Clean Energy for all Europeans Package by the EU aims, among other things, to enable collective self-consumption for various forms of energy. This step towards more prosumer-based and decentralized energy systems comes at a time when energy planning at a neighborhood scale is on the rise in many countries. It is widely assumed that—from a prosumer’s cost-perspective—shared conversion and storage technologies supplying more than a single building can be advantageous. However, it is not clear whether this is the case generally or only under certain conditions. By analyzing idealized building clusters at different degrees of urbanization (DOU), a linear-optimization approach is used to study the cost difference between shared energy infrastructure (smart energy neighborhoods, SENs) and individually planned buildings. This procedure is carried out for various emission reduction targets. The results show, that with higher emission reduction targets the advantage of SENs increases within rural environments and can reach up to 16%. Nevertheless, there are constellations in which the share of energetic infrastructure among buildings does not lead to any economic advantages. For example, in the case of building clusters with less than four buildings, almost no cost advantage is found. The result of this study underlines the importance of energy system planning within the process of urban planning.

Description: When the lightning current enters the ground through the grounding system, the impulse dispersion performance can be observed by the phenomenon of soil spark discharge, which is fundamentally determined by the nearby soil. At present, engineers use an empirical formula to convert the soil spark discharge to the impulse coefficient of impulse grounding resistance. Therefore, there is no available quantitative analysis method to evaluate soil impulse dispersion performance. To solve this problem, this paper proposes an evaluation method for the impulse discharge efficiency of soil by using X-ray images, define VI as the parameter, which is the ratio of the volume of the discharge area to the peak current. Then, the rationality and validity of the method are verified. Finally, the variation rules of impulse discharge efficiency are analyzed in different soils. Results show that the VI can reflect the change rules of impulse dispersion performance more clearly under different soil conditions, and this parameter provides a new idea for enhancing the impulse dispersion performance of soil near the grounding electrode.

Description: For this study, we conducted a decomposition analysis of industrial electricity consumption based on the logarithmic mean Divisia index approach. An empirical dataset consisting of 11 industrial sectors in Korea from 2000 to 2018 was used. The three-factor decomposition equation was extended to include four factors by decomposing the energy intensity effect into electrification and electricity consumption efficiency effects. The empirical results are summarized as follows: The increase in electricity consumption in the Korean industrial sector from 2000 to 2018 is mostly caused by the production effect. While the structure effect decreases electricity consumption, the intensity effect increases it. The key findings indicate that the hidden electrification effect can be confusing to researchers with regard to the intensity effect. The empirical evidence suggests that the intensity effect has a positive effect on electricity consumption induced by the electrification effect, although the efficiency effect continuously decreased electricity consumption. The decomposition results of some sectors show that electrification, rather than the production effect, contributed the most to the increase in electricity consumption. This implies that while replacing fuel with electricity has been successfully achieved in several sectors, there are still challenges regarding increasing energy efficiency and expanding clean electricity generation.

Description: The increasing share of distributed generation aggravates voltage limit compliance at customers’ delivery points. Currently, grid operators validate compliance with the voltage limits specified in Grid Codes by conducting load flow simulations at the medium voltage level, considering the connected low voltage grids as ‘loads’ to reduce the modeling effort. This approach does not support the accurate validation of limit compliance, as the voltage drops at the low voltage level are unknown. Nevertheless, to guarantee acceptable voltages even under worst-case conditions, safety margins are involved that impair the utilization of the electricity infrastructure. This study conducts load flows simulations in a test distribution grid, revealing the variable character of the voltage limits at different system boundaries. The conventional load model is extended by new parameters—the boundary voltage limits—to enable the consideration of variable voltage limits in load flow analysis of LINK-based smart grids. The standardized structure of the LINK-architecture allows for the systematic and accurate validation of voltage limit compliance by reducing the required modeling data to the technically necessary minimum. Use cases are specified that allows smart grids to increase the utilization of the electricity infrastructure by day-ahead scheduling and short-term adaptation of boundary voltage limits.

Description: In this study, small multilayer planar spiral coils were analyzed and optimized to wirelessly charge an in-ear wearable bio-signal monitoring device in a wine-glass-shaped transmitter (Tx) based on magnetic resonance wireless power transfer (MR-WPT). For analysis of these coils, a volume filament model (VFM) was used, and an equivalent circuit formulation for the VFM was proposed. The proposed method was applied to design effective multilayer coils with a diameter and height of 6 and 3.8 mm, respectively, in the wearable device. For the coils, a printed circuit board having a 0.6 mm thick dielectric substrate and a 2 oz thick copper metal was used. Moreover, the coils on each layer were connected in series. The dimensions of the double-, four-, and eight-layer coils were optimized for the maximum quality factor (Q-factor) and coupling efficiency. The operating frequency was 6.78 MHz. The optimal dimensions for the maximum Q-factor varied depending on the number of coil layers, pattern width, and turn number. For verification, the designed coils were fabricated and measured. For the four-layer coil, the coupling efficiency and Q-factor using the measured resistance and mutual inductance were 58.1% and 32.19, respectively. Calculations showed that the maximum Q-factor for the four-layer coil was 40.8 and the maximum coupling efficiency was 60.1%. The calculations and measurement were in good agreement. Finally, the entire system of the in-ear wearable bio-signal monitoring device, comprising a wine-glass-shaped transmitter, the designed receiving coil, and a monitoring circuit, was fabricated. The measured dc-dc efficiency of the MR-WPT system was 16.08%.

Description: The rapid changes in the services sector encourage companies to improve the processes for developing and delivering new services. An effective new service development process is not possible without planning. Business entities can plan their time, organise activities, and prioritise tasks according to the complexity or the total duration of the process. However, in the context of new service development, the planning aspect is still not sufficiently emphasised. It is noted that the aim is often to identify the factors that could reduce the duration of this process. However, there is a lack of relevant data based on certain expressions of time. The lack of such research limits the improvement of the planning processes for new service development projects. In order to evaluate the possibilities of application of the proposed new service development model for companies providing services, an empirical evaluation was conducted, using methods of expert survey, program evaluation and review, and Monte Carlo simulation. Guidelines for further research were formulated based on the obtained results.

Description: Environmental sustainability, defined as the responsibility to protect the global ecosystem in a holistic way, has become an integral factor of city strategies. Designing and implementing environment-friendly solutions to make the standard of living in cities better is indispensable for present and future generations. This article’s main objective is to identify the most environmentally friendly urban logistics measures from the perspective of urban transport system stakeholders. A multi-method approach was implemented to achieve the article’s main findings. Firstly, the literature review provided the basics for designing the research framework. Then, a three-layer methodological approach was used: The first layer included designing and carrying out the case study approach; the second layer comprised a Delphi study involving interviews with urban logistics stakeholders; and the third layer included analyzing the voices of Delphi interviewees to assess which urban logistics measures are the most important for them. The study provides an initial insight into the opinions of stakeholders for a general audience, but at the same time, also presents specific, detailed views of Tricity urban space users and decision-makers. Significant differences in opinions were observed and confirmed in the interviewed group. This study can contribute to the scientific discussion about the stakeholders’ analysis of urban logistics goals.

Description: Effective water management increases the performance of proton exchange membrane fuel cells (PEMFCs). The liquid droplet movement mechanism in the cathode channel, the gas-liquid two-phase flow pattern, and the resulting pressure drop are important to water management in PEMFCs. This work employed computational fluid dynamics (CFD) with a volume of fluid (VOF) to simulate the effects of two operating parameters on the liquid water flow in the cathode flow channel: Gas diffusion layer (GDL) pore shape for water emergence, and distance between GDL pores. From seven pore shapes considered in this work, the longer the windward side of the micropore is, the larger the droplet can grow, and the duration of droplet growth movement will be longer. In the cases of two micropores for water introduction, a critical pore distance is noted for whether two droplets coalesce. When the micropore distance was shorter than this critical value, different droplets coalesce after the droplets grew to a certain extent. These results indicate that the pore shape and the distance between pores should be accounted for in future simulations of PEMFC droplet dynamics and that these parameters need to be optimized when designing novel GDL structures.

Description: A process for obtaining ethyl levulinate through the direct esterification of levulinic acid and ethanol using AlCl3·6H2O as a catalyst was investigated. AlCl3·6H2O was very active in promoting the reaction and, the correspondent kinetic and thermodynamic data were determined. The reaction followed a homogeneous second-order reversible reaction model: in the temperature range of 318–348 K, Ea was 56.3 kJ·K−1·mol−1, whereas Keq was in the field 2.37–3.31. The activity of AlCl3·6H2O was comparable to that of conventional mineral acids. Besides, AlCl3·6H2O also induced a separation of phases in which ethyl levulinate resulted mainly (〉98 wt%) dissolved into the organic upper layer, well separated by most of the co-formed water, which decanted in the bottom. The catalyst resulted wholly dissolved into the aqueous phase (〉95 wt%), allowing at the end of a reaction cycle, complete recovery, and possible reuse for several runs. With the increase of the AlCl3·6H2O content (from 1 to 5 mol%), the reaction proceeded fast, and the phases’ separation improved. Such a behavior eventually results in an intensification of processes of reaction and separation of products and catalyst in a single step. The use of AlCl3·6H2O leads to a significant reduction of energy consumed for the final achievement of ethyl levulinate, and a simplification of line-processes can be achieved.

Description: A real case study of an energy system based on a Solar Assisted Heat Pump (SAHP) fed by hybrid photovoltaic-thermal solar panels (PVT) and seasonal storage (SS) is presented in this paper. Exergy and exergy cost analyses are proposed as complementary methods for the assessment and better understanding of the efficiency of this cogeneration solar configuration. The system performance takes advantage of storage heat in summer, when the solar resource is high in Spain, and is then later consumed during the cold winter (heating season). The building is devoted to social housing, and it is currently under construction. The assessment is based on simulations developed using TRNSYS, a dynamic simulation software for energy systems. Results show that the unit exergy cost of the solar field is around 6. The cost of the seasonal storage is higher, about 13, and its formation is affected both by its own irreversibility and by the irreversibility of the PVT solar field. The cost of the heat delivered by the heat pump is around 15, being affected by all the upstream units and even by the grid. Besides, the analysis points out strategies for improving the system efficiency, such as increasing the size of the storage tank or improving the control strategy of the boiler.

Description: Due to increasing numbers of intermittent and distributed generators in power systems, there is an increasing need for demand responses to maintain the balance between electricity generation and use at all times. For example, the electrification of transportation significantly adds to the amount of flexible electricity demand. Several methods have been developed to schedule such flexible energy consumption. However, an objective way of comparing these methods is lacking, especially when decisions are made based on incomplete information which is repeatedly updated. This paper presents a new benchmarking framework designed to bridge this gap. Surveys that classify flexibility planning algorithms were an input to define this benchmarking standard. The benchmarking framework can be used for different objectives and under diverse conditions faced by electricity production stakeholders interested in flexibility scheduling algorithms. Our contribution was implemented in a software toolbox providing a simulation environment that captures the evolution of look-ahead information, which enables comparing online planning and scheduling algorithms. This toolbox includes seven planning algorithms. This paper includes two case studies measuring the performances of these algorithms under uncertain market conditions. These case studies illustrate the importance of online decision making, the influence of data quality on the performance of the algorithms, the benefit of using robust and stochastic programming approaches, and the necessity of trustworthy benchmarking.

Description: Production of synthetic natural gas (SNG) offers an alternative way to valorize captured CO2 from energy intensive industrial processes or from a dedicated CO2 grid. This paper presents an energy-efficient way for synthetic natural gas production using captured CO2 and renewable hydrogen. Considering several renewable hydrogen production sources, a techno-economic analysis was performed to find a promising path toward its practical application. In the paper, the five possible renewable hydrogen sources (photo fermentation, dark fermentation, biomass gasification, bio photolysis, and PV electrolysis) were compared to the two reference cases (steam methane reforming and water electrolysis) from an economic stand point using key performance indicators. Possible hydrogen production capacities were also considered for the evaluation. From a technical point of view, the SNG process is an efficient process from both energy efficiency (about 57%) and CO2 conversion rate (99%). From the evaluated options, the photo-fermentation proved to be the most attractive with a levelized cost of synthetic natural gas of 18.62 €/GJ. Considering the production capacities, this option loses its advantageousness and biomass gasification becomes more attractive with a little higher levelized cost at 20.96 €/GJ. Both results present the option when no CO2 credit is considered. As presented, the CO2 credits significantly improve the key performance indicators, however, the SNG levelized cost is still higher than natural gas prices.

Description: The replacement of conventional generation sources by DER creates the need to carefully manage the reactive power maintaining the power system safe operation. The principal trend is to increase the DER volume connected to the distribution network in the coming years. Therefore, the microgrid represents an alternative to offer reactive power management due to excellent controllability features embedded in the DER, which enable effective interaction between the microgrid and the distribution network. This paper proposes a microgrid−iterative reactive power management approach of power-electronic converter based renewable technologies for day-ahead operation. It is designed to be a centralised control based on local measurements, which provides the optimal reactive power dispatch and minimise the total energy losses inside the microgrid and maintain the voltage profile within operational limits. The proposed optimal-centralised control is contrasted against seven local reactive power controls using a techno-economic approach considering the steady−state voltage profile, the energy losses, and the reactive power costs as performance metrics. Three different reactive power pricing are proposed. The numerical results demonstrate the optimal microgrid−interactive reactive power management is the most suitable techno-economic reactive power control for the day−ahead operation.

Description: The management of the distribution network is becoming increasingly important as the penetration of distributed energy resources is increasing. Reliable knowledge of the real-time status of the network is essential if algorithms are to be used to help distribution system operators define network configurations. State Estimation (SE) algorithms are capable of producing such an accurate snapshot of the network state but, in turn, require a wide range of information, e.g., network topology, real-time measurement and power profiles from customers/productions. Those profiles which may, in principle, be provided by smart meters are not always available due to technical limitations of existing Advanced Metering Infrastructure (AMI) in terms of communication, storage and computing power. That means that power profiles are only available for a subset of customers. The paper proposes an approach that can overcome these limitations: the remaining profiles, required by SE algorithms, are generated on the basis of customer-related information, identifying clusters of customers with similar features, such as the same contract and pattern of energy consumption. For each cluster, a power profile estimator is generated using long-term power profiles of a limited sub-set of customers, randomly selected from the cluster itself. The synthesized full power profile, representing each customer of the distribution network, is then obtained by scaling the power profile estimator of the cluster to which the customer belongs, by the monthly energy exchanged by that customer, data that are easily available. The feasibility of the proposed approach was validated considering the distribution grid of Unareti SpA, an Italian Distribution System Operator (DSO), operating in northern Italy and serving approximately one million customers. The application of the proposed approach to the actual infrastructure shows some limitations in terms of the accuracy of the estimation of the power profile of the customer. In particular, the proposed methodology is not fully able to properly represent clusters composed of customers with a large variability in terms of power exchange with the distribution network. In any case, the root mean square error of the synthesized full power profile with the respect to validation power profiles belonging to the same cluster is, in the worst case, on the order of 6.3%, while in the rest of cases is well below 5%. Thus, the proposed approach represents a good compromise between accuracy in representing the behavior of customers on the network and resources (in terms of computational power, data storage and communication resources) to achieve that results.

Description: Web portals have the potential to promote sustainable environmental ideas due to the capacity of digital media, such as easy accessibility, openness, and networking. Local authorities (LAs) are responsible for activating carbon savings in homes, and they are key actors when it comes to providing neutral information to their citizens. Local authority web portals may thus create environmental awareness, particularly regarding owner-occupied single-family home renovation. Nevertheless, the experiences of LAs developing web portals have rarely been studied. Therefore, this paper analyses the development process of various LA web modules and investigates how LAs foster modular web portals to stimulate the adoption of home renovation with parameters to assess LAs’ actions in terms of the management of web-modules development. A homeowner renovation journey model is applied to map current local authority developments. Case study research and interviews were done to analyse and evaluate the adoption of modular web portals developed and tested by six local authorities in four countries in Europe. Based on the development and use of the modular web portal, lessons have been derived emphasising the importance of co-creation, integrating with offline activities, and a strategic management plan.

Description: In this contribution, measurement data of phase, neutral, and ground currents from real low voltage (LV) feeders in Germany is presented and analyzed. The data obtained is used to review and evaluate common modeling approaches for LV systems. An alternative modeling approach for detailed cable and ground modeling, which allows for the consideration of typical German LV earthing conditions and asymmetrical cable design, is proposed. Further, analytical calculation methods for model parameters are described and compared to laboratory measurement results of real LV cables. The models are then evaluated in terms of parameter sensitivity and parameter relevance, focusing on the influence of conventionally performed simplifications, such as neglecting house junction cables, shunt admittances, or temperature dependencies. By comparing measurement data from a real LV feeder to simulation results, the proposed modeling approach is validated.

Description: The development of technologies for the accelerated formation or decomposition of gas hydrates is an urgent topic. This will make it possible to utilize a gas, including associated petroleum one, into a hydrate state for its further use or to produce natural gas from hydrate-saturated sediments. In this work, the effect of water content in wide range (0.7–50 mass%) and the size of quartz sand particles (porous medium;

Description: Power system inertia is an essential part of grid frequency control. The number of synchronously connected machines, which inherently provide inertia, is decreasing due to the transition to renewable energies. Conventional generation units are being replaced by renewable generation units which are connected to the grid via frequency converters. Some power systems already suffer from too little power system inertia. Hence, inertia is a valuable yet non-traded commodity. A day-ahead dispatch methodology to secure power system inertia was developed and is applied and assessed in this work. Day-ahead market data of the combined market of the Republic of Ireland and Northern Ireland is used. If the superimposition of sell and buy bids results in insufficient inertia, the dispatch algorithm is applied. In decreasing price order, non-inertia-providing sell bids get replaced by the following sell bids in the merit order. The iterative process is repeated until sufficient inertia is in the system. The provision of synthetic inertia by wind turbines is considered in the process. The costs for additional stored kinetic energy for the assessed time periods and scenarios result in costs ranging from 1.02 to 4.49 EUR/kgm2.

Description: The operating temperatures of photovoltaic (PV) modules can be impacted by the selection of specific packaging materials, e.g., backsheets and encapsulants. This research focuses on the evaluation of operating temperature reduction of one-cell modules by comparing conventional Tedlar/polyester/Tedlar (TPT) backsheet with novel thermally conductive backsheets (TCBs) materials. A large number of one-cell modules with two TCB types (TCB_A and TCB_B) and baseline TPT type were fabricated and installed in three different climatic conditions of the hot-dry desert in Arizona (high and low wind speed locations) and North Carolina (temperate with low wind speed location). In this study, these two TCBs were compared with conventional TPT backsheet in terms of performance, lifetime and levelized cost of energy (LCOE). The field results were analyzed for thermal performance of TCBs compared to TPT at three sites for two and half years. This study concludes that the thermal and electrical performances of the PV modules can be improved by using TCB_A in hot and dry climate sites and TCB_B at temperate climate sites. Therefore, the lifetime of TCB-based modules is expected to be higher than TPT-based modules. Using backsheet-specific power degradation levels and assuming the same cost for both types of backsheets, the LCOE of modules using TCBs is estimated to be lower than that of TPT.

Description: A while-drilling energy harvesting device is designed in this paper to recovery energy along with the longitudinal vibration of the drill pipes, aiming to serve as a continuous power supply for downhole instruments during the drilling procedure. Radial size of the energy harvesting device is determined through the drilling engineering field experience and geological survey reports. A piezoelectric coupling model based on the selected piezoelectric material was established via COMSOL Multiphysics numerical simulation. The forced vibration was analyzed to determine the piezoelectric patch length range and their best installation positions. Modal analysis and frequency response research indicate that the natural frequency of the piezoelectric cantilever beam increased monotonously with the increase of the piezoelectric patch’ thickness before reaching an inflection point. Moreover, the simulation results imply that the peak voltage of the harvested energy varied in a regional manner with the increase of the piezoelectric patches. When the thickness of the piezoelectric patches was 1.2–1.4 mm, the designed device gained the best energy harvest performance with a peak voltage of 15–40 V. Works in this paper provide theoretical support and design reference for the application of the piezoelectric material in the drilling field.

Description: Accurate and timely macro forecasting requires new and powerful predictors. Carbon emissions data with high trading frequency and short releasing lag could play such a role under the framework of mixed data sampling regression techniques. This paper explores the China case in this regard. We find that our multiple autoregressive distributed lag model with mixed data sampling method setup outperforms either the auto-regressive or autoregressive distributed lag benchmark in both in-sample and out-of-sample nowcasting for not only the monthly changes of the purchasing managers’ index in China but also the Chinese quarterly GDP growth. Moreover, it is demonstrated that such capability operates better in nowcasting than h-step ahead forecasting, and remains prominent even after we account for commonly-used macroeconomic predictive factors. The underlying mechanism lies in the critical connection between the demand for carbon emission in excess of the expected quota and the production expansion decision of manufacturers.

Description: This paper focuses on the performance analysis of a sensorless control for a Doubly Fed Induction Generator (DFIG) in grid-connected operation for turbine-based wind generation systems. With reference to a conventional stator flux based Field Oriented Control (FOC), a full-order adaptive observer is implemented and a criterion to calculate the observer gain matrix is provided. The observer provides the estimated stator flux and an estimation of the rotor position is also obtained through the measurements of stator and rotor phase currents. Due to parameter inaccuracy, the rotor position estimation is affected by an error. As a novelty of the discussed approach, the rotor position estimation error is considered as an additional machine parameter, and an error tracking procedure is envisioned in order to track the DFIG rotor position with better accuracy. In particular, an adaptive law based on the Lyapunov theory is implemented for the tracking of the rotor position estimation error, and a current injection strategy is developed in order to ensure the necessary tracking sensitivity around zero rotor voltages. The roughly evaluated rotor position can be corrected by means of the tracked rotor position estimation error, so that the corrected rotor position is sent to the FOC for the necessary rotating coordinate transformation. An extensive experimental analysis is carried out on an 11 kW, 4 poles, 400 V/50 Hz induction machine testifying the quality of the sensorless control.

Description: Gold nanoparticles (Au NPs) play a significant role in science and technology because of their unique size, shape, properties and broad range of potential applications. This review focuses on the various approaches employed for the synthesis, modification and functionalization of nanostructured Au. The potential catalytic applications and their enhancement upon modification of Au nanostructures have also been discussed in detail. The present analysis also offers brief summaries of the major Au nanomaterials synthetic procedures, such as hydrothermal, solvothermal, sol-gel, direct oxidation, chemical vapor deposition, sonochemical deposition, electrochemical deposition, microwave and laser pyrolysis. Among the various strategies used for improving the catalytic performance of nanostructured Au, the modification and functionalization of nanostructured Au produced better results. Therefore, various synthesis, modification and functionalization methods employed for better catalytic outcomes of nanostructured Au have been summarized in this review.

Description: Quantitate characterization of pore structures is fundamental to elucidate fluid flow in the porous media. Pore structures of the Lucaogou Formation in the Jimsar Sag were investigated using petrography, mercury intrusion capillary porosimetry (MICP) and X-ray computed tomography (X-ray μ-CT). MICP analyses demonstrate that the pore topological structure is characterized by segmented fractal dimensions. Fractal dimension of small pores (r 〈 Rapex) ranges from 2.05 to 2.37, whereas fractal dimension of large pores (r 〉 Rapex) varies from 2.91 to 5.44, indicating that fractal theory is inappropriate for the topological characterization of large pores using MICP. Pore volume of tight reservoirs ranges over nine orders of magnitude (10−1–108 μm3), which follows a power-law distribution. Fractal dimensions of pores larger than a lower bound vary from 1.66 to 2.32. Their consistence with MICP results suggests that it is an appropriate indicator for the complex and heterogeneous pore network. Larger connected pores are primary conductive pathways regardless of lithologies. The storage capacity depends largely on pore complexity and heterogeneity, which is negatively correlated with fractal dimension of pore network. The less heterogeneous the pore network is, the higher storage capability it would have; however, the effect of pore network heterogeneity on the transport capability is much more complicated.

Description: This paper proposes a novel adaptive intelligent global sliding mode control for the tracking control of a DC-DC buck converter with time-varying uncertainties/disturbances. The proposed control law is formulated using a switching surface that eliminates the reaching phase and ensures the existence of the sliding action from the start. The control law is derived based on the Lyapunov stability theory. The effectiveness of the proposed approach is illustrated via high-fidelity simulations by means of Simscape simulation environment in MATLAB. Satisfactory tracking accuracy, efficient suppression of the chattering phenomenon in the control input, and high robustness against uncertainties/disturbances are among the attributes of the proposed control approach.

Description: This paper presents the preliminary results of our research activity aimed at forecasting the number of voltage sags in distribution networks. The final goal of the research is to develop proper algorithms that the network operators could use to forecast how many voltage sags will occur at a given site. The availability of four years of measurements at Italian Medium Voltage (MV) networks allowed the statistical analyses of the sample voltage sags without performing model-based simulations of the electric systems in short-circuit conditions. The challenge we faced was to overcome the barrier of the extremely long measurement times that are considered mandatory to obtain a forecast with adequate confidence. The method we have presented uses the random variable time to next event to characterize the statistics of the voltage sags instead of the variable number of sags, which usually is expressed on an annual basis. The choice of this variable allows the use of a large data set, even if only a few years of measurements are available. The statistical characterization of the measured voltage sags by the variable time to next event requires preliminary data-conditioning steps, since the voltage sags that are measured can be divided in two main categories, i.e., rare voltage sags and clusters of voltage sags. Only the rare voltage sags meet the conditions of a Poisson process, and they can be used to forecast the performance that can be expected in the future. However, the clusters do not have the characteristics of memoryless events because they are sequential, time-dependent phenomena the occurrences of which are due to exogenic factors, such as rain, lightning strikes, wind, and other adverse weather conditions. In this paper, we show that filtering the clusters out from all the measured sags is crucial for making successful forecast. In addition, we show that a filter, equal for all of the nodes of the system, represents the origin of the most important critical aspects in the successive steps of the forecasting method. In the paper, we also provide a means of tracking the main problems that are encountered. The initial results encouraged the future development of new efficient techniques of filtering on a site-by-site basis to eliminate the clusters.

Description: A microgrid’s self-consumption rate reflects its ability to retain its own energy and decrease its reliance on the synchronous grid. This paper investigates the empirical case of a microgrid equipped with photovoltaic (PV) panels and identifies challenges in engaging the microgrid’s users to increase their self-consumption. Accordingly, we explored both the physical and social dimensions of the microgrid. The former involved mapping the electricity consumption and production through an exploratory data analysis, and evaluating the associated price signals, while the latter involved the use of design interventions to explore users’ perceptions of the system. We highlight the problem of price signal impedance, the need for cost reflective pricing and the challenge in designing and extending internal price models in settings with various actors. We address the limitations of price signals, alongside alternative unidimensional signals, and emphasize the need for an integrated approach to a user engagement strategy as well as the challenges that this approach entails. Our results shed light on the complexity of energy communities such as microgrids, and why their implementation can introduce multidimensional challenges that demand cross-disciplinary approaches.

Description: The current paper evaluates the thermal performance of immersion cooling for an Electric Vehicle (EV) battery module comprised of NCA-chemistry based cylindrical 21700 format Lithium-ion cells. Efficacy of immersion cooling in improving maximum cell temperature, cell’s temperature gradient, cell-to-cell temperature differential, and pressure drop in the module are investigated by direct comparison with a cold-plate-cooled battery module. Parametric analyses are performed at different module discharge C-rates and coolant flow rates to understand the sensitivity of each cooling strategy to important system performance parameters. The entire numerical analysis is performed using a validated 3D time-accurate Computational Fluid Dynamics (CFD) methodology in STAR-CCM+. Results demonstrate that immersion cooling due its higher thermal conductance leads to a lower maximum cell temperature and lower temperature gradients within the cells at high discharge rates. However, a higher rate of heat rejection and poor thermal properties of the dielectric liquid results in a much higher temperature non-uniformity across the module. At lower discharge rates, the two cooling methods show similar thermal performance. Additionally, owing to the lower viscosity and density of the considered dielectric liquid, an immersion-cooled battery module performs significantly better than the cold-plate-cooled module in terms of both coolant pressure drop.

Description: In light of global warming and the energy turn, sector coupling has gained increasing interest in recent years, from both the scientific community and politics. In the following article it is hypothesized that efficient multifaceted sector coupling solutions depend on detailed spatial and temporal characteristics of energy demand and supply. Hence, spatiotemporal modelling is used as a methodology of integrated spatial and energy planning, in order to determine favourable sector coupling strategies at the local level. A case study evaluation was carried out for both central and decentral renewable energy sources. Considering the high temporal resolutions of energy demand and supply, the results revealed a feasible operation of a district heating network in the central areas of the case study municipalities. Additionally, building integrated solar energy technologies are capable of providing large amount of excess energy that could serve other demand sectors, such as the mobility sector, or could be used for Power-to-X solutions. It is suggested that sector coupling strategies require spatial considerations and high temporal comparisons, in order to be reasonably integrated in spatial and urban planning.

Description: Improving the accuracy of the slurry flow predictions in different operating flow regimes remains a major focus for multiphase flow research, and it is especially targeted at industrial applications such as oil and gas. In this paper we develop a robust integrated method consisting of an artificial neural network (ANN) and support vector regression (SVR) to estimate the critical velocity, the slurry flow regime change, and ultimately, the frictional pressure drop for a solid–liquid slurry flow in a horizontal pipe, covering wide ranges of flow and geometrical parameters. Three distinct datasets were used to develop machine learning models with totals of 100, 325, and 125 data points for critical velocity, and frictional pressure drops for heterogeneous and bed-load regimes respectively. For each dataset, 80% of the data were used for training and the rest 20% for evaluating the out of sample performance. The K-fold technique was used for cross-validation. The prediction results of the developed integrated method showed that it significantly outperforms the widely used existing correlations and models in the literature. Additionally, the proposed integrated method with the average absolute relative error (AARE) of 0.084 outperformed the model developed without regime classification with the AARE of 0.155. The proposed integrated model not only offers reliable predictions over a wide range of operating conditions and different flow regimes for the first time, but also introduces a general framework of how to utilize prior physical knowledge to achieve more reliable performances from machine learning methods.

Description: Photovoltaic (PV) technology allows large-scale investments in a renewable power-generating system at a competitive levelized cost of electricity (LCOE) and with a low environmental impact. Large-scale PV installations operate in a highly competitive market environment where even small performance losses have a high impact on profit margins. Therefore, operation at maximum performance is the key for long-term profitability. This can be achieved by advanced performance monitoring and instant or gradual failure detection methodologies. We present in this paper a combined approach on model-based fault detection by means of physical and statistical models and failure diagnosis based on physics of failure. Both approaches contribute to optimized PV plant operation and maintenance based on typically available supervisory control and data acquisition (SCADA) data. The failure detection and diagnosis capabilities were demonstrated in a case study based on six years of SCADA data from a PV plant in Slovenia. In this case study, underperforming values of the inverters of the PV plant were reliably detected and possible root causes were identified. Our work has led us to conclude that the combined approach can contribute to an efficient and long-term operation of photovoltaic power plants with a maximum energy yield and can be applied to the monitoring of photovoltaic plants.

Description: Among the super insulating materials, aerogel has interesting properties: very low thermal conductivity and density, resistance to high temperatures and transparency. It is a rather expensive material, but incentives in the field can improve its economic attractiveness. Starting from this, the thermal behavior of a test building entirely insulated with aerogel panels was investigated through an extended experimental campaign. A dynamic simulation model of a case study building was generated to better comprehend the energy savings obtained through aerogel in terms of energy demand over a whole year. The investigation was completed by computing the carbon and energy payback times of various retrofit strategies through a life cycle assessment approach, as well as by a cost-benefit analysis through a probabilistic financial framework. Compared to conventional insulation materials, aerogel is characterized by a higher energy and carbon payback time, but it guarantees better environmental performance in the whole life cycle. From an economic-financial perspective, the aerogel retrofit is the best in the current tax incentive scenario. However, due to its higher lump-sum investment, aerogel’s net present value is very sensitive to tax deductions, and it is riskier than the best comparable materials in less favorable tax scenarios.

Description: The unknown NOx distributions inside large-scale CFB (circulating fluidized bed) boilers have always hindered the economy of the SNCR (selective non-catalytic reduction) process. In this study, field tests were carried out on a typical 300 MW CFB boiler, where multi-level 316 L-made probe and Ecom-J2KN/Testo 350 analyzers were used to perform detailed two-dimensional distributions of flue gas composition at SNCR inlets for the first time. The penetration depth inside the horizontal flue pass was up to 7 m. The NOx distributions were analyzed in detail combining with the auxiliary test in the dilute phase zone. Key results show that the average O2 concentrations in #A and #C regions were 6.52% and 0.95%, respectively. The vertical NOx distributions of #A and #C SNCR inlets were similar, showing a trend of first increasing and then decreasing with peak value all appeared at 5 m depth, while the NOx distribution of #B SNCR inlet was basically increasing. Some local areas with extremely high NOx concentration (over 2000 mg/m3) were observed near the inclined edge of SNCR inlets, which has never been reported before. Based on this, the optimization of urea injections was conducted, which could save 15.7% of the urea solution consumption while ensuring ultra-low emission of NOx.

Description: Building Integrated Photovoltaic (BIPV) modules are a new type of photovoltaic (PV) modules that are widely used in distributed PV stations on the roof of buildings for power generation. Due to the high installation location, BIPV modules suffer from lightning hazard greatly. In order to evaluate the risk of lightning stroke and consequent damage to BIPV modules, the studies on the lightning attachment characteristics and the lightning energy withstand capability are conducted, respectively, based on numerical and experimental methods in this paper. In the study of lightning attachment characteristics, the numerical simulation results show that it is easier for the charges to concentrate on the upper edge of the BIPV metal frame. Therefore, the electric field strength at the upper edge is enhanced to emit upward leaders and attract the lightning downward leaders. The conclusion is verified through the long-gap discharge experiment in a high voltage lab. From the experimental study of multi-discharge in the lab, it is found that the lightning interception efficiency of the BIPV module is improved by 114% compared with the traditional PV modules. In the study of lightning energy withstand capability, a thermoelectric coupling model is established. With this model, the potential, current and temperature can be calculated in the multi-physical field numerical simulation. The results show that the maximum temperature of the metal frame increases by 16.07 °C when 100 kA lightning current flows through it and does not bring any damage to the PV modules. The numerical results have a good consistency with the experimental study results obtained from the 100 kA impulse current experiment in the lab.

Description: In Korea apartment buildings, most energy is consumed as heating energy. In order to reduce heating energy in apartment buildings, it is required to reduce the amount of energy used in heating systems. Energy saving in heating systems can be achieved through operation and control based on efficient operation plans. The efficient operation plan of the heating system should be based on the predicted heating load. Thus, various methods have been developed for predicting heating loads. Recently, artificial intelligence techniques (e.g., ANN: artificial neural network) have been used to predict heating loads. The process for determination of input data variables is necessary to obtain the accuracy of predicted results using an ANN model. However, there is a lack of studies to evaluate the accuracy level of the predicted results caused by the selection and combination of input variables. There is a need to evaluate the performance of an ANN model for prediction of residential heating loads. Therefore, the purpose of this study is, for a residential building, to evaluate the accuracy levels of predicted heating loads using an ANN model with various combinations of input variables. To achieve the study purpose, each case was classified according to the combination of the input variables and the prediction results were analyzed. Through this, the worst, mean, and best were selected according to the predicted performance. In addition, an actual case was selected consisting of variables that can be measured in an actual building. The derived cv(RMSE) of each case resulted in a percentage value of 38.2% for the worst, 7.3% for the mean, 3.0% for the best, and 5.4% for the actual. The largest difference between the best and worst resulted in 33.2%, and thus the precision of the predicted heating loads was highly affected by the selection and combination of the input variables used for the ANN model.

Description: Accurate and real-time acquisition of vehicle state parameters is key to improving the performance of vehicle control systems. To improve the accuracy of state parameter estimation for distributed drive electric vehicles, an unscented Kalman filter (UKF) algorithm combined with the Huber method is proposed. In this paper, we introduce the nonlinear modified Dugoff tire model, build a nonlinear three-degrees-of-freedom time-varying parametric vehicle dynamics model, and extend the vehicle mass, the height of the center of gravity, and the yaw moment of inertia, which are significantly influenced by the driving state, into the vehicle state vector. The vehicle state parameter observer was designed using an unscented Kalman filter framework. The Huber cost function was introduced to correct the measured noise and state covariance in real-time to improve the robustness of the observer. The simulation verification of a double-lane change and straight-line driving conditions at constant speed was carried out using the Simulink/Carsim platform. The results show that observation using the Huber-based robust unscented Kalman filter (HRUKF) more realistically reflects the vehicle state in real-time, effectively suppresses the influence of abnormal error and noise, and obtains high observation accuracy.

Description: A novel high-resolution method for forecasting cloud motion from all-sky images using deep learning is presented. A convolutional neural network (CNN) was created and trained with more than two years of all-sky images, recorded by a hemispheric sky imager (HSI) at the Institute of Meteorology and Climatology (IMUK) of the Leibniz Universität Hannover, Hannover, Germany. Using the haze indexpostprocessing algorithm, cloud characteristics were found, and the deformation vector of each cloud was performed and used as ground truth. The CNN training process was built to predict cloud motion up to 10 min ahead, in a sequence of HSI images, tracking clouds frame by frame. The first two simulated minutes show a strong similarity between simulated and measured cloud motion, which allows photovoltaic (PV) companies to make accurate horizon time predictions and better marketing decisions for primary and secondary control reserves. This cloud motion algorithm principally targets global irradiance predictions as an application for electrical engineering and in PV output predictions. Comparisons between the results of the predicted region of interest of a cloud by the proposed method and real cloud position show a mean Sørensen–Dice similarity coefficient (SD) of 94 ± 2.6% (mean ± standard deviation) for the first minute, outperforming the persistence model (89 ± 3.8%). As the forecast time window increased the index decreased to 44.4 ± 12.3% for the CNN and 37.8 ± 16.4% for the persistence model for 10 min ahead forecast. In addition, up to 10 min global horizontal irradiance was also derived using a feed-forward artificial neural network technique for each CNN forecasted image. Therefore, the new algorithm presented here increases the SD approximately 15% compared to the reference persistence model.

Description: This paper proposes a multi-objective load dispatch algorithm based on economic predictive control to solve the real-time multi-objective load dispatch problem of biomass heat and power cogeneration. According to the energy conservation law and production process, a real-time multi-objective load dispatch optimization model for heat and power units is established. Then, the concept of multi-objective utopia points is introduced, and the multi-objective load comprehensive objective function is defined to coordinate the conflict between the economic performance and pollutant emission performance of the units. Furthermore, using the online receding optimization characteristics of economic predictive control, the comprehensive objective function of multi-objective load dispatching is optimized online. Then, the fuel rate satisfying the economic performance and pollutant emission performance of the units is calculated to realize the economic performance and environmental protection operation of biomass heat and power cogeneration. Finally, the proposed multi-objective load dispatch control method is compared to traditional dispatch strategies by using industrial data. The results show that the method presented here can well balance the production cost and pollutant emission objective under the fluctuation of the thermoelectric load demand, and provides a feasible scheme for real-time dispatching of the multi-objective load dispatch problem of biomass heat and power cogeneration.

Description: Transonic flows of a molecularly complex organic fluid through a stator cascade were investigated by means of large eddy simulations (LESs). The selected configuration was considered as representative of the high-pressure stages of high-temperature Organic Rankine Cycle (ORC) axial turbines, which may exhibit significant non-ideal gas effects. A heavy fluorocarbon, perhydrophenanthrene (PP11), was selected as the working fluid to exacerbate deviations from the ideal flow behavior. The LESs were carried out at various operating conditions (pressure ratio and total conditions at inlet), and their influence on compressibility and viscous effects is discussed. The complex thermodynamic behavior of the fluid generates highly non-ideal shock systems at the blade trailing edge. These are shown to undergo complex interactions with the transitional viscous boundary layers and wakes, with an impact on the loss mechanisms and predicted loss coefficients compared to lower-fidelity models relying on the Reynolds-averaged Navier–Stokes (RANS) equations.

Description: Data-driven diagnosis methods for faults of proton exchange membrane fuel cell (PEMFC) systems can diagnose faults through the state variable data collected during the operation of the PEMFC system. However, the state variable data collected from the PEMFC system during the stack switching between different operating points can easily cause false alarms, such that the practical value of the diagnosis system is reduced. To overcome this problem, a fault diagnosis method for PEMFC systems based on steady-state identification is proposed in this paper. The support vector data description (SVDD) and relevance vector machine (RVM) optimized by the artificial bee colony (ABC) are used for the steady-state identification and fault diagnosis. The density-based spatial clustering of applications with noise (DBSCAN) and linear least squares fitting (LLSF) are used to identify the abnormal data in datasets and estimate change rates of the system state variables respectively. The proposed method can automatically identify the state variable data collected from the PEMFC system during the stack switching between different operating points, so that the diagnosis accuracy can be improved and false alarms can be reduced. The proposed method has a certain practical value and can provide a reference for further study.

Description: Power converters in wind turbines exhibit frequent failures, the causes of which have remained unexplained for years. Field-experience based research has revealed that power- and thermal-cycling induced fatigue effects in power electronics do not contribute significantly to the field failures observed. Instead, clear seasonal failure patterns point to environmental influences, in particular to humidity, as a critical stressor and likely driver of converter failure. In addition to the electrical operating conditions, it is therefore important to also identify and characterize the climatic conditions that power converters in wind turbines are exposed to, both as a contribution to root-cause analysis and as a basis for the derivation of suitable test procedures for reliability qualification of components and systems. This paper summarizes the results of field-measurement campaigns in 31 wind turbines of seven different manufacturers spread over three continents. The temperature and humidity conditions inside the converter cabinets are characterized and related to the environmental conditions of the turbines and to their operation. The cabinet-internal climate is found to be subject to pronounced seasonal variations. In addition to the site-specific ambient climatic conditions and the operation of the turbines, the converter cooling concept is identified to significantly influence the climatic conditions inside the power cabinets.

Description: The European Union aims to reduce Greenhouse Gas (GHG) emissions by 55% before 2030 compared to 1990 as a reference year. One of the main contributions to GHG emissions comes from the household sector. This paper shows that the household sector, when organised into a form of prosumer microgrids, including renewable sources for electric, heating and cooling energy supply, can be efficiently decarbonised. This paper investigates one hypothetical prosumer microgrid with the model RES2GEO (Renewable Energy Sources to Geothermal). The aim is to integrate a carbon-free photovoltaic electricity source and a shallow geothermal reservoir as a heat source and heat sink during the heating and cooling season. A total of four cases have been evaluated for the Zagreb City location. The results represent a balance of both thermal and electric energy flows within the microgrid, as well as thermal recuperation of the reservoir. The levelised cost of energy for all cases, based on a 20-year modelling horizon, varies between 41 and 63 EUR/MWh. On the other hand, all cases show a decrease in CO2 emissions by more than 75%, with the best case featuring a reduction of more than 85% compared to the base case, where electricity and gas for heating are supplied from the Distribution System Operator at retail prices. With the use of close integration of electricity, heating and cooling demand and supply of energy, cost-effective decarbonisation can be achieved for the household sector.

Description: This paper presents an analysis of methods to increase the efficiency of heat transfer in heat exchangers. The scope of the research included analysis of efficiency optimization using the example of two tubular heat exchanger structures most often used in industry. The obtained efficiency of heat recovery from the ground of the examined exchangers was over 90%, enabling the reduction of emissions of the heating systems of buildings. The paper presents the results of tests of two types of heat pipes using R134A, R404A, and R407C working agents. The paper also presents the results of experimental tests using the R410A working medium. The results included in the study will also enable the effective use of land as a heat store.

Description: Permanent magnet machines with segmented stator cores are affected by additional harmonic components of the cogging torque which cannot be minimized by conventional methods adopted for one-piece stator machines. In this study, a novel approach is proposed to minimize the cogging torque of such machines. This approach is based on the design of multiple independent shapes of the tooth tips through a topological optimization. Theoretical studies define a design formula that allows to choose the number of independent shapes to be designed, based on the number of stator core segments. Moreover, a computationally-efficient heuristic approach based on genetic algorithms and artificial neural network-based surrogate models solves the topological optimization and finds the optimal tooth tips shapes. Simulation studies with the finite element method validates the design formula and the effectiveness of the proposed method in suppressing the additional harmonic components. Moreover, a comparison with a conventional heuristic approach based on a genetic algorithm directly coupled to finite element analysis assesses the superiority of the proposed approach. Finally, a sensitivity analysis on assembling and manufacturing tolerances proves the robustness of the proposed design method.

Description: A detailed analysis of the power demand of an ultraefficient lightweight-battery electric vehicle is performed. The aim is to overcome the problem of lightweight electric vehicles that may have a relatively bad environmental impact if their power demand is not extremely reduced. In particular, electric vehicles have a higher environmental impact during the production phase, which should be balanced by a lower impact during the service life by means of a lightweight design. As an example of an ultraefficient electric vehicle, a prototype for the Shell Eco-marathon competition is considered. A “tank-to-wheel” multiphysics model (thermo-electro-mechanical) of the vehicle was developed in “Matlab-Simscape”. The model includes the battery, the DC motors, the motor controller and the vehicle drag forces. A preliminary model validation was performed by considering experimental data acquisitions completed during the 2019 Shell Eco-marathon European competition at the Brooklands Circuit (UK). Numerical simulations are employed to assess the sharing of the energy consumption among the main dissipation sources. From the analysis, we found that the main sources of mechanical dissipation (i.e., rolling resistance, gravitational/inertial force and aerodynamic drag) have the same role in the defining the power consumption of such kind of vehicles. Moreover, the effect of the main vehicle parameters (i.e., mass, aerodynamic coefficient and tire rolling resistance coefficient) on the energy consumption was analyzed through a sensitivity analysis. Results showed a linear correlation between the variation of the parameters and the power demand, with mass exhibiting the highest influence. The results of this study provide fundamental information to address critical decisions for designing new and more efficient lightweight vehicles, as they allow the designer to clearly identify which are the main parameters to keep under control during the design phase and which are the most promising areas of action.

Description: In Poland, special attention is focused on sustainable municipal waste management. As a result, new waste incineration plants are being planned. They are considered to be modern, ecologically friendly, and renewable energy sources. The waste from conventional incineration, which contains hazardous substances, must be disposed of in an appropriate manner. This study used advanced statistical tools, such as control charts, trend analysis, and time series analysis. The analysis was based on the leachability of selected elements and chemical compounds in incineration bottom ashes (IBAs) from the Waste to Energy Plant in Kraków, which were weathered for 2 weeks. The analysis was performed for 34 weeks. The obtained leachability results were compared with the leachability limit values of individual components. Based on the analysis of the control charts, it was found that in the case of selected samples, the leachability limit values for processing outside the plant using the R5 recovery process (LLVR5) values were exceeded. Seasonality analysis was performed using the autocorrelation function (ACF), the partial autocorrelation function (PACF), and the frequency analysis. Based on the obtained results, it was concluded that the leachability of elements and chemical compounds from waste does not confirm the occurrence of seasonality. It was found that from the exceedances of the LLVR5 mean that the two-week weathering is not sufficient and further studies should be carried out. The research methodology, which was presented on the example of the leachability of elements and compounds from IBA, can also be used for other waste analyses.

Description: In the battery management system, it is important to accurately and efficiently estimate the state of charge (SOC) of lithium-ion batteries, which generally requires the establishment of a equivalent circuit model of the battery, whose accuracy and rationality play an important role in accurately estimating the state of lithium-ion batteries. The traditional single order equivalent circuit models do not take into account the changes of impedance spectrum under the action of multiple factors, nor do they take into account the balance of practicality and complexity of the model, resulting the low accuracy and poor practicability. In this paper, the theory of electrochemical impedance spectroscopy is used to guide and improve the equivalent circuit model. Based on the analysis of the variation of the high and intermediate frequency range of the impedance spectrum with the state of charge and temperature of the battery, a variable order equivalent model (VOEM) is proposed by Arrhenius equation and Bayesian information criterion (BIC), and the state equation and observation equation of VOEM are improved by autoregressive (AR) equations. Combined with the unscented Kalman filter (UKF), a SOC online estimation method is proposed, named VOEM-AR-UKF. The experimental results show that the proposed method has high accuracy and good adaptability.

Description: Measurement accuracy is an important performance indicator for high-voltage direct current (HVDC) voltage dividers. The temperature rise effect for a HVDC voltage divider’s internal resistance has an adverse effect on measurement accuracy. In this paper, by building a solid model of a DC voltage divider, the internal temperature rise characteristic and error caused by the temperature rise in a resistance voltage divider were theoretically simulated. We found that with the increase in height and working time, the internal temperature of the voltage divider increased. The results also showed that the lowest temperature was near the lower flange and the highest temperature was near the upper flange in the middle of the voltage divider. The error caused by the temperature rise increased first and then decreased gradually with divider height, increasing with its working time. The measurement error caused by the internal temperature difference in steady state reached a maximum of 158.4 ppm. This study provides a theoretical basis to determine the structure and accuracy improvement for a resistive voltage divider, which is helpful for the selection of components and the optimization of the heat dissipation structure.

Description: With the increasing depth of coal mining, the quantitative evaluation of the degree of geological structure development is becoming increasingly important for the control of mine water hazards in coal mining areas. Understanding the complexity of geological structure development can improve the safety and efficiency of coal production. At present, various evaluation indicators of the geological structure development cannot fully reflect the complexity of faults and folds, and the evaluation process is usually affected by subjective human factors. In this paper, the fractal dimension from fractal theory is used as the evaluation indicator to quantitatively analyze and evaluate the complexity of fault and fold structure in the mining area. To verify the evaluation results, the mathematical geology method is applied in an analysis of the trend surface of fault and fold networks. The results indicate that the fractal dimension can be applied for the quantitative analysis and evaluation of the complexity of fault and fold networks. In addition, the outcome of this work provides new insights into how to characterize the fault and fold structures of coal mining areas in northern China, and has some important implications to ensure the coal production safety.

Description: New guidelines set by international organizations for refrigeration companies cause that natural working fluids such as carbon dioxide are increasingly used in new refrigeration systems. Carbon dioxide (R-744) is used in freezing, cooling, or air conditioning installations, in which the cooling load fluctuates hourly. To adapt the cooling capacity of the evaporator to the current cooling load of the cooled space, a number of control elements are used. The paper proposes a new method of regulating the cooling capacity for a one-stage refrigeration cycle with the R-744 refrigerant and an internal heat exchanger (IHX). The proposed method involves using an additional evaporator and combines the possibility of regulating the cooling capacity with the possibility of energy efficiency ratio (EER) improvement. The energy analysis of the proposed method of regulating the cooling capacity was performed and the results were compared with the control method. The control method was using the compressor hot gas bypass valve which allows the flow of hot vapor refrigerant to the suction side. The energy analysis was carried out for both subcritical and supercritical cycles using the energy equations. For each of the considered methods, the characteristics of the change in the EER as a function of the reduction of the cooling capacity in both supercritical and subcritical cycles were determined. It was found that when the cooling capacity decreased by 50%, the hot gas bypass regulating method was around 30% less efficient compared to the proposed additional evaporator regulating method.

Description: This paper discusses the question of heat flux distribution between bristle package and rotor during a rubbing event. A three-dimensional Computational Fluid Dynamics (3D CFD) model of the brush seal test rig installed at the Institute of Thermal Turbomachinery (ITS) was created. The bristle package is modelled as a porous medium with local non-thermal equilibrium. The model is used to numerically recalculate experimentally conducted rub tests on the ITS test rig. The experimentally determined total frictional power loss serves as an input parameter to the numerical calculation. By means of statistical evaluation methods, the ma in influences on the heat flux distribution and the maximum temperature in the frictional contact are determined. The heat conductivity of the rotor material, the heat transfer coefficients at the bristles and the rubbing surface were identified as the dominant factors.

Description: Cellulosic fibers from date palm are among the most promising lignocellulose feedstock for biorefinery purposes. The world production is between 1.9 and 2.4 million t/year. Initially, a pretreatment with dilute-sulphuric acid of these fibers was performed using a response surface methodology, with temperature and process time as factors. The aim is to produce bioethanol from young and old fibers from date palm, Phoenix dactylifera L. Optimal thermochemical pretreatment conditions for both fibers palms were 220 °C in hydrothermal conditions (without acid); in these conditions pretreated young fibers presented a maximum content in holocelluloses of 45.18% and old fibers 61.97%. Subsequently, during the enzymatic hydrolysis a maximum yield of total reducing sugars (TRS) was reached, 46.32 g/100 g for pretreated dry young fibers and 48.54 g/100 g for pretreated dry old fibers. After enzymatic saccharification, hydrolysates were fermented by Pachysolen tannophilus (ATCC 32691) to ethanol, reaching yields (YE/TRS) of 37.94 g ethanol/100 g of TRS for young fibers and 35.84 g ethanol/100 g of TRS for old fibers. Globally, considering the full process, in the fermentation of the hydrolysates, a yield (YE) of 10.64 g ethanol/100 g of dry young fibers and 10.88 g ethanol/100 g of dry old fibers was reached.

Description: In the 21st century, it is becoming increasingly clear that human activities and the activities of enterprises affect the environment. Therefore, it is important to learn about the methods in which companies minimize the negative effects of their activities. The article presents the steps taken and innovative actions carried out by enterprises in the energy sector. The article analyzes innovative activities undertaken and implemented by enterprises from the energy sector. The relationships between innovative strategies, including, inter alia, digitization, and Industry 4.0 solutions, in the development of companies and the achieved results concerning sustainable development and environmental impact. Digitization has far exceeded traditional productivity improvement ranges of 3–5% per year, with a clear cost improvement potential of well above 25%. Enterprises on a large scale make attempts to increase energy efficiency by implementing the state-of-the-art innovative technical and technological solutions, which increase reliability and durability (material and mechanical engineering). Digitization of energy companies allows them to reduce operating costs and increases efficiency. With digital advances, the useful life of an energy plant can be increased up to 30%. Advanced technologies, blockchain, and the use of intelligent networks enables the activation of prosumers in the electricity market. Reducing energy consumption in industry and at the same time increasing energy efficiency for which the European Union is fighting in the clean air package for all Europeans have a positive impact on environmental protection, sustainable development, and the implementation of the decarbonization program.

Description: In this paper, discrete time reaching law-based sliding mode control of continuous time systems is considered. In sliding mode control methods, usually the assumption of bounded absolute values of disturbances is used. However in many cases, the rate of change of the disturbance is also bounded. In the presented approach, this knowledge is used to improve the control precision and reduce the undesirable chattering. Another advantage of the proposed method is that the disturbance does not have to satisfy the matching conditions. In the paper two new reaching laws are analyzed, one of them ensures the switching quasi-sliding motion and the other the non-switching motion. For both of them, the robustness is assessed by calculating the quasi-sliding mode band width, as well as the greatest possible state error values. Specifically, the state errors are not considered only at the sampling instants, as is usual for discrete time systems, but the bounds on the continuous values “between” the sampling instants are also derived. Then, the proposed approaches are compared and analyzed with respect to energy expenditure of the control signal.

Description: The rising demand for lower noise emissions of car ancillary units due to electrification and higher customer expectations regarding driving comfort results in the need for more silent car components. Hydraulic driven car components in particular are often identified as a major source of noise in the system. Therefore, it is mandatory to investigate the noise sources inside the hydraulic system. In this work, a combined CFD-FEM approach is applied to estimate the flow-induced noise radiation of a mechanically driven transmission pump. To achieve this goal, the mapping procedure to hand over the pressure field from the CFD to the FEM mesh must be valid. For this purpose, the error during the mapping process is evaluated and different parameters, which influence the mapping results, are analyzed. Additionally, the impact of the time step size and the length of the time signal on the frequency resolution of the force signal is investigated to get an appropriate excitation force for the vibroacoustic simulation. Subsequently, a force analysis and a structural FEM simulation are performed to identify which flow phenomenon contributes most to the excitation of the pump housing. Specific locations in the pump with high loads are pointed out. In a final step, the results of the vibroacoustic model are compared to acceleration and sound pressure level measurements of the pump performed in a hemi-anechoic room.

Description: Modern energy automation solutions and demand response applications rely on load profiles to monitor and manage electricity consumption effectively. The introduction of smart control systems capable of handling additional fuzzy parameters, such as weather data, through machine learning methods, offers valuable insights in an attempt to adjust consumer behavior optimally. Following recent advances in the field of fuzzy control, this study presents the design and implementation of a fuzzy control system that processes environmental data in order to recommend minimum energy consumption values for a residential building. This system follows the forward chaining Mamdani approach and uses decision tree linearization for rule generation. Additionally, a hybrid feature selector is implemented based on XGBoost and decision tree metrics for feature importance. The proposed structure discovers and generates a small set of fuzzy rules that highlights the energy consumption behavior of the building based on time-series data of past operation. The response of the fuzzy system based on sample input data is presented, and the evaluation of its performance shows that the rule base generation is derived with improved accuracy. In addition, an overall smaller set of rules is generated, and the computation is faster compared to the baseline decision tree configuration.

Description: During the day, photovoltaic (PV) systems are exposed to different sunlight conditions in addition to partial shading (PS). Accordingly, maximum power point tracking (MPPT) techniques have become essential for PV systems to secure harvesting the maximum possible power from the PV modules. In this paper, optimized control is performed through the application of relatively newly developed optimization algorithms to PV systems under Partial Shading (PS) conditions. The initial value of the duty cycle of the boost converter is optimized for maximizing the amount of power extracted from the PV arrays. The emperor penguin optimizer (EPO) is proposed not only to optimize the initial setting of duty cycle but to tune the gains of controllers used for the boost converter and the grid-connected inverter of the PV system. In addition, the performance of the proposed system based on the EPO algorithm is compared with another newly developed optimization technique based on the cuttlefish algorithm (CFA). Moreover, particle swarm optimization (PSO) algorithm is used as a reference algorithm to compare results with both EPO and CFA. PSO is chosen since it is an old, well-tested, and effective algorithm. For the evaluation of performance of the proposed PV system using the proposed algorithms under different PS conditions, results are recorded and introduced.

Description: In this work we assessed the shallow geothermal heat-exchange potential of a fluvial plain of the Central Apennines, the lower Metauro Valley, where about 90,000 people live. Publicly available geognostic drilling data from the Italian Seismic Microzonation studies have been exploited together with hydrogeological and thermophysical properties of the main geological formations of the area. These data have been averaged over the firsts 100 m of subsoil to define the thermal conductivity, the specific heat extraction rates of the ground and to establish the geothermal potential of the area (expressed in MWh y−1). The investigation revealed that the heat-exchange potential is mainly controlled by the bedrock lithotypes and the saturated conditions of the sedimentary infill. A general increase in thermal conductivity, specific heat extraction and geothermal potential have been mapped moving from the coast, where higher sedimentary infill thicknesses have been found, towards the inland where the carbonate bedrock approaches the surface. The geothermal potential of the investigated lower Metauro Valley is mostly between ~9.0 and ~10 MWh y−1 and the average depth to be drilled to supply a standard domestic power demand of 4.0 kW is ~96 m (ranging from 82 to 125 m all over the valley). This investigation emphasizes that the Seismic Microzonation studies represent a huge database to be exploited for the best assessment of the shallow geothermal potential throughout the Italian regions, which can be addressed by the implementation of heating and cooling through vertical closed-loop borehole heat exchanger systems coupled with geothermal heat pumps.

Description: Accurate and comprehensive methods for the assessment of radiated electromagnetic emissions in modern electric transportation systems are a necessity. The characteristics and susceptibility of modern victim signaling and communication radio services, operating within and outside the right-of-way, require an update of the measurement methods integrating or replacing the swept frequency technique with time domain approaches. Applicable standards are the EN 50121 (equivalent to the IEC 62236) and Urban Mass Transport Association (UMTA) with additional specifications from project contracts. This work discusses the standardized methods and settings, and the representative operating conditions, highlighting areas where improvements are possible and opportune (statistical characterization of measurement results, identification and distinction of emissions and line resonances, and narrowband and broadband phenomena). In particular for the Electromagnetic Compatibility (EMC) assessment with new Digital Communication Systems, the characterization of time distribution of spectral properties is discussed, e.g., by means of Amplitude Probability Distribution and including time distribution information. The problem of determination of site and setup uncertainty and repeatability is also discussed, observing on one hand the lack of clear indications in standards and, on the other hand, the non-ideality and intrinsic variability of measurement conditions (e.g., rolling stock operating conditions, synchronization issues, and electric arc intermittence).

Description: The present work addresses the need for an efficient, versatile, accurate and open-source numerical tool to be used during the design stage of wave energy converters (WECs). The device considered here is the heaving point-absorber developed and tested by Sandia National Laboratories. The smoothed particle hydrodynamics (SPH) method, as implemented in DualSPHysics, is proposed since its meshless approach presents some important advantages when simulating floating devices. The dynamics of the power take-off system are also modelled by coupling DualSPHysics with the multi-physics library Project Chrono. A satisfactory matching between experimental and numerical results is obtained for: (i) the heave response of the device when forced via its actuator; (ii) the vertical forces acting on the fixed device under regular waves and; (iii) the heave response of the WEC under the action of both regular waves and the actuator force. This proves the ability of the numerical approach proposed to simulate accurately the fluid–structure interaction along with the WEC’s closed-loop control system. In addition, radiation models built from the experimental and WAMIT results are compared with DualSPHysics by plotting the intrinsic impedance in the frequency domain, showing that the SPH method can be also employed for system identification.

Description: Recently, the use of electric vehicles in a power grid has been attracting attention. The success of vehicle-grid integration (VGI) requires the active participation of not only VGI service providers but also electric vehicle owners, utility companies, and the government in the VGI service. However, until now, such research has not been sufficiently discussed. Thus, we propose a framework for analyzing the economic environment in which each stakeholder can participate, especially in the application of a demand response, and derive its economic value in Korea. Also, through the proposed framework, we suggest optimal scenarios and policy directions for each participant’s successful business. Our results show that government and a utility company need to share their benefits with a VGI service provider to make VGI a success.

Description: Smart-meter technology advancements have resulted in the generation of massive volumes of information introducing new opportunities for energy services and data-driven business models. One such service is non-intrusive load monitoring (NILM). NILM is a process to break down the electricity consumption on an appliance level by analyzing the total aggregated data measurements monitored from a single point. Most prominent existing solutions use deep learning techniques resulting in models with millions of parameters and a high computational burden. Some of these solutions use the turn-on transient response of the target appliance to calculate its energy consumption, while others require the total operation cycle. In the latter case, disaggregation is performed either with delay (in the order of minutes) or only for past events. In this paper, a real-time NILM system is proposed. The scope of the proposed NILM algorithm is to detect the turning-on of a target appliance by processing the measured active power transient response and estimate its consumption in real-time. The proposed system consists of three main blocks, i.e., an event detection algorithm, a convolutional neural network classifier and a power estimation algorithm. Experimental results reveal that the proposed system can achieve promising results in real-time, presenting high computational and memory efficiency.

Description: In August 2019, a new bus fleet of 36 electric and 58 hybrid buses were implemented in Trondheim, Norway. This paper examines the carbon footprint of electrified city buses, by addressing the achieved and potential reduction for the new bus fleet. Important aspects such as geographical location of production, charging electricity mix, and impact from production and operation on lifetime emissions, are also examined. A meta-analysis on life cycle assessment studies was undertaken to investigate greenhouse gas emissions and energy demand in different parts of bus production. This is followed by the production of a bus model using the findings and comparing electrified buses with diesel and HVO buses. The models were then used in a case study of the bus fleet in Trondheim, to understand the specific parameters affecting the carbon footprint. The results show that the overall carbon footprint has been considerably reduced (37%) by implementing biofuel and electrified buses, and that a further reduction of 52% can be achieved through full electrification. The operation emissions for the fleet were found to be 49 g CO2-eq/person-km, which is lower than the average city bus and passenger car in Norway.

Description: The integrated electricity–gas energy system (IEGES) coordinates the power system and natural gas system through P2G equipment, gas turbines and other coupling components. The IEGES can realize wide-range and long-distance transmission of electricity, heat and natural gas, and truly realize large-scale cross-regional energy supply in space. At present, the theoretical system applicable to the comprehensive benefit evaluation of the IEGES has not been established, and the economic, environmental and social benefits of the system are still at a preliminary study stage. Therefore, the comprehensive benefit evaluation model of the IEGES is constructed, and the integrated benefit evaluation indicator system of the IEGES is designed along the investment and planning, energy supply, equipment operation, power distribution and terminal user. Through the combination of subjective and objective indicator weighting methods, the weights of each indicator are clarified and the matter-element extension theory (MEE) is used to improve the technique for order preference by similarity to ideal solution (TOPSIS), and the comprehensive benefit evaluation model of the IEGES is established. Finally, taking Beijing Yanqing IEGES, Tianjin Eco-city No. 2 Energy Station and Hebei IEGES III as an example, the practicability and effectiveness of the evaluation indicator system and model are verified.

Description: This work examines formate salts as potential phase change materials (PCMs) for middle-high temperature (≤250 °C) latent heat thermal energy storage applications. The thermophysical properties of three formate salts were characterized: pure sodium formate and binary blends of sodium/potassium formate and sodium/calcium formate. The stability of formate PCM’s was evaluated by thermal cycling using differential scanning calorimetry where sodium formate and sodium/potassium formate appeared stable over 600 cycles, while sodium/calcium formate exhibited a monotonic decrease in heat of fusion over the test period. A longer test with sodium formate led to gas release and decomposition of the salt. FTIR analysis of the PCM showed degradation of formate to oxalate. T-history experiments with 50-g PCM quantities demonstrated a bulk supercooling of only 2–3 °C for these salts. Thermal conductivity enhancement of over 700% was achieved by embedding aluminum in the solid PCM. Finally, mild carbon steel was immersed in molten sodium formate for up to 2000 h. Sodium formate was found to be non-corrosive, as calculated by mass loss and confirmed by cross-sectional high-resolution microscopy. FTIR analysis of the PCM after 2000 h shows oxidation at the free surface, while the bulk PCM remained unchanged, further indicating a need to protect the formate from atmospheric exposure when used as a PCM.

Description: This paper proposes a Electro-Magnetic Transient (EMT) model of a 2 GW offshore network with the parallel operation of two Modular Multi-level Converter (MMC)—High Voltage Direct Current (HVDC) transmission links connecting four Offshore Wind Farms (OWFs) to two onshore systems, which represent a large scale power system. Additionally, to mitigate the challenges corresponding to voltage and frequency stability issues in large scale offshore networks, a Direct Voltage Control (DVC) strategy is implemented for the Type-4 Wind Generators (WGs), which represent the OWFs in this work. The electrical power system is developed in the power system simulation software RSCADTM, that is suitable for performing EMT based simulations. The EMT model of 2 GW offshore network with DVC in Type-4 WGs is successfully designed and it is well-coordinated between the control structures in MMCs and WGs.

Description: Microentrepreneurs contribute to the growth of electromobility, and hence to sustainable transport, by the purchase of alternative fuel vehicles (AFV). This article attempts to identify key factors that may affect the growth of interest in AFV among microentrepreneurs. To find the key factors, data from 181 Polish microenterprises was collected and analyzed by means of the factor analysis. The results showed that in contrary to the popular opinion, it is not the price of the car that is crucial for its purchase, but the information that leads to knowledge about technical and utility values, and to legal and economic predictability.

Description: The State of Charge (SOC) estimation is a significant issue for safe performance and the lifespan of Lithium-ion (Li-ion) batteries. In this paper, a Robust Adaptive Online Long Short-Term Memory (RoLSTM) method is proposed to extract SOC estimation for Li-ion Batteries in Electric Vehicles (EVs). This real-time, as its name suggests, method is based on a Recurrent Neural Network (RNN) containing Long Short-Term Memory (LSTM) units and using the Robust and Adaptive online gradient learning method (RoAdam) for optimization. In the proposed architecture, one sequential model is defined for each of the three inputs: voltage, current, and temperature of the battery. Therefore, the three networks work in parallel. With this approach, the number of LSTM units are reduced. Using this suggested method, one is not dependent on precise battery models and can avoid complicated mathematical methods. In addition, unlike the traditional recursive neural network where content is re-written at any time, the LSTM network can decide on preserving the current memory through the proposed gateways. In that case, it can easily transfer this information over long paths to receive and maintain long-term dependencies. Using real databases, the experiment results illustrate the better performance of RoLSTM applied to SOC estimation of Li-Ion batteries in comparison with a neural network modeling and unscented Kalman filter method that have been used thus far.

Description: In many circles, brown coal continues to be viewed as a cheap source of energy, resulting in numerous investments in new opencast brown coal mines. Such a perception of brown coal energy is only possible if the external costs associated with mining and burning coal are not considered. In past studies, external cost analysis has focused on the external costs of coal burning and associated emissions. This paper focuses on the extraction phase and assesses the external costs to agriculture associated with the resulting depression cone. This paper discusses the difficulties researchers face in estimating agricultural losses resulting from the development of a depression cone due to opencast mineral extraction. In the case of brown coal, the impacts are of a geological, natural-climatic, agricultural-productive, temporal, and spatial nature and result from a multiplicity of interacting factors. Then, a methodology for counting external costs in crop production was proposed. The next section estimates the external costs of crop production arising from the operation of opencast mines in the Konin-Turek brown coal field, which is located in central Poland. The analyses conducted showed a large decrease in grain and potato yields and no effect of the depression cone on sugar beet levels. Including the estimated external costs in the cost of producing electricity from mined brown coal would significantly worsen the profitability of that production.

Description: In this paper, a switched-capacitor multilevel inverter with voltage boosting and common-mode-voltage reduction capabilities is put forth. The proposed inverter is synthesized with one-half bridge and several switched-capacitor cells. Due to the voltage boosting and common-mode current reduction features, the proposed multilevel inverter is suitable for grid-connected PV applications. In addition, an analytical lifetime evaluation based on mission profile of the proposed inverter has been presented to derive lifetime distribution of semiconductors. Whereas in the proposed inverter, any components failure can bring the whole system to a shutdown. The series reliability model is used to estimate the lifetime of the overall system. The performance of the suggested multilevel inverter in grid-connected applications is verified through the simulation results using the grid-tied model in Matlab/Simulink. Moreover, the viability and feasibility of the presented inverter are proven by using a one kW lab-scaled prototype.