Construction is a key sector for green growth on a global scale [...]

The EU policymakers have adopted legislation to support communities taking responsibility for the energy transition. However, their development and integration are still in their early stages: many studies are performed without considering the overlapped social, economic, political, electrical, and information technology tasks simultaneously. This paper is the first to look at energy communities in their entirety, from the roles of the actors to the organisation, regulation, technical solution, and the market, to the use and business cases. The waterfall methodology was used throughout the work. The results show that energy communities can be viable by becoming reliable players so DSOs can better integrate the acquired flexibility and other services into their processes without compromising power supply. Their technical integration requires a coordinated operation and control of the entire power grid, including transmission and distribution, and the end-users, as proposed by the LINK h... [more]

Nuclear power is a type of clean and green energy; however, there is a risk of radioactive material leakage when accidents occur. When radioactive material leaks from nuclear power plants, it has a great impact on the environment and personnel safety. In order to enhance the safety of nuclear power plants and support the operator’s decisions under accidental circumstances, this paper proposes a fault diagnosis method for nuclear power plants based on the sparrow search algorithm (SSA) optimized by the CNN-LSTM network. Firstly, the convolutional neural network (CNN) was used to extract features from the data before they were then combined with the long short-term memory (LSTM) neural network to process time series data and form a CNN-LSTM model. Some of the parameters in the LSTM neural network need to be manually tuned based on experience, and the settings of these parameters have a great impact on the overall model results. Therefore, this paper selected the sparrow search algorithm... [more]

Combustion is the most commonly used technology to produce energy from biomass; nevertheless, there are still thermal efficiency problems in current biomass combustion furnaces and a lack of knowledge about the properties of residual biomasses that could be used as fuels. Aiming to contribute to knowledge of the potential of residual biomass for energy generation, this work reports on the implementation of a 2D computational model to study the combustion performance of several solid biomass fuels, and its application in the analysis of Lippia origanoides bagasse combustion. The model uses an Eulerian−Lagrangian approach; in the continuous phase, governing equations are solved, and in the dispersed phase, particles are tracked and the mass, momentum, species and energy transfer between the phases are calculated. The model was validated against experimental data from a combustor fueled by three biomasses: wood pellets, olive stone and almond shell. The results show deviations of less tha... [more]

This work focuses on the enhancement of the charging reliability of both scheduled (SEVs) and opportunistic (UEVs) electric vehicle (EV) users in an EV fast charging station (FCS). The proposed charging coordination strategies allow UEVs to exploit unused charging resources to optimally utilize the limited charging resources of FCS. However, the optimum utilization of limited charging resources of an FCS while assuring a reliable charging process for plugged-in EVs under random failures of electric vehicle supply equipment (EVSE) is a real challenge for the FCS controller. When the FCS admits UEVs in addition to SEVs, assuring a satisfactory quality of service to both EV user categories is also dispensable. Therefore, we analyze the performance of reservation of off-board mobile chargers (MOBCs) to enhance the charging reliability of EV users while achieving high charging resource utilization. This work proposes resource allocation and charging coordination strategies for an FCS where... [more]

Islands face unique challenges on their journey towards achieving carbon neutrality by the mid-century, due to the lack of energy interconnections, limited domestic energy resources, extensive fossil fuel dependence, and high load variance requiring new technologies to balance demand and supply. At the same time, these challenges can be turned into a great opportunity for economic growth and the creation of jobs with non-interconnected islands having the potential to become transition frontrunners by adopting sustainable technologies and implementing innovative solutions. This paper uses an advanced energy−economy system modeling tool (IntE3-ISL) accompanied by plausible decarbonization scenarios to assess the medium- and long-term impacts of energy transition on the energy system, emissions, economy, and society of the island of Mayotte. The model-based analysis adequately captures the specificities of Mayotte and examines the complexity, challenges, and opportunities to decarbonize t... [more]

This paper aims to review one of the least used, but no less important, approaches in the assessment of the environmental implications of electricity generation: the Economic Input-Output Life Cycle Assessment (EIO-LCA). This methodology is a top-down approach intertwined with the environmental satellite accounts provided by the national statistical office. Through the use of economic input-output (IO) tables and industrial sector-level environmental and energy data, the EIO-LCA analysis allows for broad impact coverage of all sectors directly and indirectly involved with electricity generation. In this study, a brief overview of this methodology and the corresponding assumptions is presented, as well as an updated review of the different applications of the EIO-LCA approach in electricity generation, suggesting a possible classification of the many studies developed in this context. The different ways of overcoming the problem of disaggregation in the electricity sector are also addre... [more]

The reliability of pumping units at nuclear power plants (NPPs) is critical in terms of their energy efficiency and safety. Remarkably, WWER-1000 reactors at Ukrainian NPPs are equipped with outdated pumping units that have already served their full-service life. This fact leads to an urgent need to develop a new, more efficient pump. In the article, a promising pump, ACNA 600-35, was developed. It was designed to increase the energy efficiency of pumps TX 800/70/8-K-2E, applied at the holding pool and the industrial circuit of the nuclear reactor. Since these pumps should be imported from the monopoly suppliers, this affects both the energy efficiency of pumping equipment and the energy independence of Eastern Europe. The proposed pump ACNA 600-35 is characterized by an increased efficiency of up to 0.12−0.13 compared with the TX 800/70/8-K-2E pump. In general, the life cycle cost of the proposed pump is 15−20% lower than for the analog TX 800/70/8-K-2E. The design of the developed pu... [more]

Accurate localization of partial discharge in GIS equipment remains a key focus of daily maintenance for substations, which can be achieved through advanced detection and location techniques, as well as regular maintenance and testing of the equipment. However, there is currently an issue with low accuracy in the localization algorithm. Aiming at the problems of low precision and local optimization of the swarm intelligence algorithm in partial discharge localization system of GIS equipment, this paper proposes a 3D localization algorithm based on a time difference of arrival (TDOA) model of the improved artificial fish swarm algorithm (IAFSA). By introducing the investigation behaviour of the artificial bee colony(ABC) algorithm into the artificial fish swarms algorithm (AFSA), this algorithm is more efficient to jump out of the local extremum, enhance the optimization performance, improve the global search ability and overcome the premature convergence. Furthermore, more precise posi... [more]

Allotropes of carbon are responsible for discovering the three significant carbon-based compounds, fullerene, carbon nanotubes, and graphene. Over the last few decades, groundbreaking graphene with the finest two-dimensional atomic structure has emerged as the driving force behind new research and development because of its remarkable mechanical, electrical, thermal, and optical functionalities with high surface area. Synthesis of graphene oxide (GO) and reduced graphene oxide (rGO) has resulted in numerous applications that previously had not been possible, incorporating sensing and adsorbent properties. Our study covers the most prevalent synthetic methods for making these graphene derivatives and how these methods impact the material’s main features. In particular, it emphasizes the application to water purification, CO2 capture, biomedical, potential energy storage, and conversion applications. Finally, we look at the future of sustainable utilization, its applications, and the cha... [more]

The uncertainty of output makes it difficult to effectively solve the economic security dispatching problem of the power grid when a high proportion of renewable energy generating units are integrated into the power grid. Based on the proximal policy optimization (PPO) algorithm, a safe and economical grid scheduling method is designed. First, constraints on the safe and economical operation of renewable energy power systems are defined. Then, the quintuple of Markov decision process is defined under the framework of deep reinforcement learning, and the dispatching optimization problem is transformed into Markov decision process. To solve the problem of low sample data utilization in online reinforcement learning strategies, a PPO optimization algorithm based on the Kullback−Leibler (KL) divergence penalty factor and importance sampling technique is proposed, which transforms on-policy into off-policy and improves sample utilization. Finally, the simulation analysis of the example show... [more]

Numerous recent innovations have been achieved with the goal of enhancing electric vehicles and the parts that go into them, particularly in the areas of managing energy, battery design and optimization, and autonomous driving. This promotes a more effective and sustainable eco-system and helps to build the next generation of electric car technology. This study offers insights into the most recent research and advancements in electric vehicles (EVs), as well as new, innovative, and promising technologies based on scientific data and facts associated with e-mobility from a technological standpoint, which may be achievable by 2030. Appropriate modeling and design strategies, including digital twins with connected Internet of Things (IoT), are discussed in this study. Vehicles with autonomous features have the potential to increase safety on roads, increase driving economy, and provide drivers more time to focus on other duties thanks to the Internet of Things idea. The enabling technolog... [more]

Global warming, pollution, and the depletion of fossil fuels have compelled human beings to explore alternate sources of energy and cleaner modes of transport. In recent years, renewable energy sources (RES) have been massively introduced to the grid. Furthermore, Electric Vehicles (EVs) are becoming popular as a cleaner mode of transport. However, the introduction of RESs and EVs to the grid has imposed additional challenges on the grid operators because of their random nature. This review aims to focus on the integration of RES and EVs to the grid, thereby presenting the global status of RESs and EVs, the impact of integrating RESs and EVs to the grid, the challenges of integrating RES and EV to the grid, optimization techniques for EV and RES integration to the grid, and mitigation techniques. A total of 153 research papers are meticulously reviewed, and the findings are put forward in this review. Thus, this review will put forward the latest developments in the area of EV and RES... [more]

Synchronous stability in power systems is of essential importance for system safety and operation. For the phase-locked loop (PLL)-based synchronous stability in power electronic-based power systems, which has recently stimulated interest in researchers in the field of electrical power engineering, but is still controversial, this paper divides the topic into two aspects, including the PLL device stability and the system stability. It is found that the PLL device is always stable and the error between the PLL output angle θpll and the terminal voltage angle θt is always finite. Therefore, the synchronization of power electronic-based power systems should be understood as the output synchronization between the electrical rotation vectors (θt or θpll) from each item of grid-tied equipment, rather than the synchronization of the PLL device itself. In addition, it is found that θpll plays an active role in the system synchronization dynamics not only in electromagnetic timescales but also... [more]

This study proposes an approach to obtain maximum power via wireless power transfer using a single primary-side capacitor. It is shown that higher power is achieved when compared to the common wireless power transfer circuit under resonance with dual (primary- and secondary-side) capacitors. This approach is divided into three phases. By choosing the capacitor and frequency as freely assignable variables, we symbolically obtain a formula that allows us to determine the optimized capacitance and frequency for maximum power. To verify our method, we used a numerical analysis and compared it with an electronic circuit simulation. The symbolic formula is able to maintain maximum power despite changes in load or in the coupling coefficients.

The single pole-to-ground (SPG) fault is one of critical failures which will have a serious impact on the stable operation of the multi-terminal DC distribution network based on the modular multilevel converter (MMC). It is very significant to analyze fault characteristics for detecting faults and protection design. This paper established the DC SPG fault model, which showed that in the presence of a reactor, the short-circuit current was reduced from 2.3 kA to 1 kA at 6 ms after the fault. Then, a novel SPG fault protection strategy was proposed, which detected the current derivative in connection transformer grounding branch. When the value increases past the threshold of current derivative, small resistance was switched on to increase fault current. Thus, the reliability of differential protection was enhanced. Compared with the traditional protection method, the proposed method does not need communication, and improved the speed of protection. Finally, the simulation model was esta... [more]

This study focuses on the important issue of predicting electricity load for efficient energy management. To achieve this goal, different statistical methods were compared, and results over time were analyzed using various ratios and layers for training and testing. This study uses an artificial neural network (ANN) model with advanced prediction techniques such as genetic algorithms (GA) and adaptive neuro-fuzzy inference systems (ANFIS). This article stands out with a comprehensive compilation of many features and methodologies previously presented in other studies. This study uses a long-term pattern in the prediction process and achieves the lowest relative error values by using hourly divided annual data for testing and training. Data samples were applied to different algorithms, and we examined their effects on load predictions to understand the relationship between various factors and electrical load. This study shows that the ANN−GA model has good accuracy and low error rates f... [more]

The internal pressure and temperature of type IV on-board hydrogen storage cylinders constantly change during the hydrogen fast-filling process. In this work, a 2D axisymmetric computational fluid dynamics (CFD) model is established to study the temperature rise of hydrogen storage cylinders during the fast-filling process. The hydrogen filling rate, ambient temperature, volume, and hydrogen inlet temperature were investigated to evaluate their effects on temperature rise inside the cylinders. The effects of the inlet pressure rise and pre-cooling patterns on the temperature rise of large-volume type IV hydrogen storage cylinders are analyzed, and the optimal filling strategy is determined. The research results show that a greater filling rate causes a higher hydrogen temperature rise at the end. The ambient temperature increases linearly with the maximum hydrogen temperature and decreases linearly with the state of charge (SOC). As the volume increases, the temperature rise of the cyl... [more]

The availability and accessibility of renewable energy in locations worldwide make it play a leading role in the decarbonization process of the energy sector [...]

The review contains a comparative analysis of studies on the production of hydrogen and syngas based on the processes of partial oxidation of natural gas and other types of gas feedstock. The results presented in the literature show the high potential of non-catalytic autothermal processes of partial oxidation of hydrocarbons for the development of gas chemistry and energetics. The partial oxidation of hydrocarbons makes it possible to overcome such serious shortcomings of traditional syngas production technologies as technological complexity and high energy and capital intensity. The features of non-catalytic partial oxidation of hydrocarbon gases, the obtained experimental results and the results of kinetic modeling of various options for the implementation of the process, which confirm the adequacy of the kinetic mechanisms used for the analysis, are considered in detail. Examples of industrial implementation of processes based on partial oxidation and proposed alternative options f... [more]

The building sector has traditionally accounted for about 40% of global energy-related carbon dioxide (CO2) emissions, as compared to other end-use sectors. Due to this fact, as part of the global effort towards decarbonization, significant resources have been placed on the development of technologies, such as active buildings, in an attempt to achieve reductions in the respective CO2 emissions. Given the uncertainty around the future level of the corresponding CO2 emissions, this work presents an approach based on machine learning to generate forecasts until the year 2050. Several algorithms, such as linear regression, ARIMA, and shallow and deep neural networks, can be used with this approach. In this context, forecasts are produced for different regions across the world, including Brazil, India, China, South Africa, the United States, Great Britain, the world average, and the European Union. Finally, an extensive sensitivity analysis on hyperparameter values as well as the applicati... [more]

Microencapsulated phase change slurry (MEPCS), prepared by mixing microencapsulated phase change materials (MEPCMs) with water or other carrier fluids, is widely used in different applications such as for thermal regulation or heat storage systems. The transient thermal-hydraulic behavior accompanying the phase change process of the MEEPCS has a significant impact on the system performance. However, the heat and mass transfer during the phase change of the MEPCS is a complex multiscale process, due to the complex phase change of small particles and the complex coupling between the particles and carrier fluids. The numerical methods have been proved to be efficient and powerful means to investigate such complex phase change problems. However, the mathematical model is the critical factor determining the accuracy of the numerical methods, and is still under development. This review summarized the mathematical models proposed for the thermal-hydraulic processes of the MEPCS, compared the... [more]

In micro-grids (MGs), renewable energy resources (RESs) supply a major portion of the consumer demand. The intermittent nature of these RESs and the stochastic characteristics of the loads cause a frequency stabilization issue in MGs. Owing to this, in the present manuscript, the authors try to uncover the frequency stabilization/regulation issue (FRI) in a two-area MG system comprising wind turbines (WTs), an aqua-electrolyzer, a fuel cell, a bio-gas plant, a bio-diesel plant, diesel generation (DG), ship DG, electric vehicles and their energy storage devices, flywheels, and batteries in each control area. With these sources, the assessment of the FRI is carried out using different classical controllers, namely, the integral (I), proportional plus I (PI), and PI plus derivative (PID) controllers. The gain values of these I, PI, and PID controllers are tuned using the recently proposed smell agent optimization (SAO) algorithm. The simulation studies reveal the outstanding performance o... [more]

Microgrids have become an alternative for integrating distributed generation to supply energy to isolated communities, so their control and optimal management are important. This research designs and simulates the three levels of control of a DC microgrid operating in isolated mode and proposes an Energy Management System (EMS) based on Model Predictive Control (MPC), with real-time measurement feedback for optimal energy dispatch, which ensures power flow distribution and operation at minimum cost while extending the lifespan of the BESS. The EMS can react to disturbances produced in the lower control levels. The microgrid’s performance is analyzed and compared in two scenarios without EMS, and with EMS against changes in irradiation and changes in electricity demand. The fulfillment of the power balance is evaluated by analyzing the power delivered by each generation unit, the operating cost, and the state of charge of the battery (SOC).

The impact of gravity on the particle preferential concentration is investigated by direct numerical simulations in an Eulerian−Lagrangian framework for a large range of Stokes numbers Stη=0.01∼4. For particles with small Stokes numbers such as Stη=0.01, the gravity has minor effects on the particle spatial distribution in the turbulence. With increasing Stη, stripped structures of the high number density of particles appear and expand along the gravity direction. Different evaluation methods of particle preferential concentration are discussed such as the spatial distribution, the box index, and the probability density function. The number density of particles in the accumulating regions reduced under the influence of gravity. The reduction becomes prominent for the particle cloud at Stokes number Stη≈1, especially in the clusters of high particle number density. For large Stokes number Stη, the slip velocity significantly increases due to the particle gravity. Due to the gravity, the... [more]