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This paper examines the potential of solar and hydrogen (H 2) energy-based hybrid energy systems for residential applications. The growing need for energy and the demand for sustainable energy sources have led to the development of integrated energy systems that combine renewable energy resources to meet energy needs. This paper overviews recent studies on hybrid energy systems for on-grid and off-grid residential utilizations. It discusses the system configuration and components of hybrid energy systems, including solar panels, electrolyzers, fuel cells (FC), and batteries. It also covers the technical optimization of integrated energy systems, including sizing, control strategies, and economic analysis. The key findings of this review paper indicate that hybrid energy systems can offer dependable and sustainable energy for residential applications. Through numerical analyses, the optimal dimensioning of the system elements and control strategies can significantly enhance the system's performance and lower the cost of energy. This study also highlights the challenges and opportunities for integrating hybrid energy systems within residential applications. Overall, it provides in-depth perspectives on the possibilities inherent in solar and hydrogen energy-based hybrid energy systems for residential applications. The findings can guide future research and the advancement of hybrid energy systems for sustainable energy solutions. • Comprehensive review on solar and hydrogen-based residential applications. • Holistic approach to system configuration, optimization, and economics. • Detailed analysis of interconnected components enhancing system efficiency. • Unique focus on real-world residential applications and scenarios. • Broad applicability across diverse geographical regions. [ABSTRACT FROM AUTHOR]

With the urgent global need to limit warming to 2 °C as well as a localized need in our case study to address rising energy demand amid electrical and thermal network limitations, a critical examination of demand-side energy reductions and the concept of energy sufficiency is needed. This paper contributes to the sparse literature on bottom-up analysis by utilizing Iceland—a leader in renewable energy generation—as a case study to explore the socio-economic factors influencing energy footprints. Our findings reveal significant energy footprints across various consumption domains, particularly housing and mobility, influenced by income levels, urbanization, and lifestyle choices. The study highlights the paradox of a high renewable energy supply leading to potential misconceptions regarding abundant and low-cost energy, resulting in substantial energy consumption-related environmental impacts. Using detailed household consumption survey data, this research provides insights crucial for developing sustainable energy policies that not only target technological advancements but also address the need for a reduction in energy demand and a shift towards energy sufficiency. This work marks a contribution to the literature through the provision of a case study of low income inequality and high energy footprints in a highly renewable energy system context. Further, this work is useful for Icelandic and international policymakers to understand in such high-demand contexts which consumption domains would be most relevant for sufficiency policies. This comprehensive analysis opens pathways for future research to further explore the intersections of energy consumption, socio-economic factors, and well-being, offering a nuanced understanding necessary for crafting sufficiency and demand-side policies aimed at a sustainable energy future. [ABSTRACT FROM AUTHOR]

The variability and intermittency inherent in renewable energy sources poses significant challenges to balancing power supply and demand, often leading to wind and solar energy curtailment. To address these challenges, this paper focuses on enhancing Time of Use (TOU) electricity pricing strategies. We propose a novel method based on equivalent load, which leverages typical power grid load and incorporates a responsibility weight for renewable energy consumption. The responsibility weight acts as an equivalent coefficient that accurately reflects renewable energy output, which facilitates the division of time periods and the development of a demand response model. Subsequently, we formulate an optimized TOU electricity pricing model to increase the utilization rate of renewable energy and reduce the peak–valley load difference of the power grid. To solve the TOU pricing optimization model, we employ the Social Network Search (SNS) algorithm, a metaheuristic algorithm simulating users' social network interactions to gain popularity. By incorporating the users' mood when expressing opinions, this algorithm efficiently identifies optimal pricing solutions. Our results demonstrate that the equivalent load-based method not only encourages renewable energy consumption but also reduces power generation costs, stabilizes the power grid load, and benefits power generators, suppliers, and consumers without increasing end users' electricity charges. [ABSTRACT FROM AUTHOR]

The green transition is a challenge for the Polish economy and energy sector. In this paper, the expert method of analysis was applied and findings revealed that the challenges and prerequisites for an effective transformation of the power sector mainly include technical, technological and organizational issues of energy production and use. The provision of electricity at competitive prices and with a low carbon footprint, for individual consumers and industry, is a prerequisite for maintaining the well-being of the population and ensuring the competitiveness of domestically produced goods. The ambitious climate policy goals of the European Union require immediate action and call for radical changes in the Polish energy sector; in the coming years, it must drastically reduce the amount of energy produced from fossil fuels and replace it with so-called green energy from renewable sources. The main purpose of this article was to highlight the need to modify Poland's energy policy until 2040 in order to make it more consistent with the ambitious climate goals of the European Union. This article also shows that Poland's energy transition must include a shift from fossil fuels to renewables, while ensuring that energy security is stabilized by the current energy and generation resources. To this end, we discuss the issues of creating reserves in the national energy system for the entire period of Poland's energy transition. [ABSTRACT FROM AUTHOR]

Microgrid technology offers a new practical approach to harnessing the benefits of distributed energy resources in grid-connected and island environments. There are several significant advantages associated with this technology, including cost-effectiveness, reliability, safety, and improved energy efficiency. However, the adoption of renewable energy generation and electric vehicles in modern microgrids has led to issues related to stability, energy management, and protection. This paper aims to discuss and analyze the latest techniques developed to address these issues, with an emphasis on microgrid stability and energy management schemes based on both traditional and distinct approaches. A comprehensive analysis of various schemes, potential issues, and challenges is conducted, along with an identification of research gaps and suggestions for future microgrid development. This paper provides an overview of the current state of the field and proposes potential areas of future research. [ABSTRACT FROM AUTHOR]

Global energy consumption has led to concerns about potential supply problems, energy consumption and growing environmental impacts. This paper comprehensively provides a detailed assessment of current studies on the subject of building integrated photovoltaic (BIPV) technology in net-zero energy buildings (NZEBs). The review is validated through various case studies, which highlight the significance of factors such as building surface area to volume ratio (A/V), window-wall ratio (WWR), glass solar heating gain coefficient (SHGC), and others in achieving the NZEBs standards. In addition, this review article draws the following conclusions: (1) NZEBs use renewable energy to achieve energy efficiency and carbon neutrality. (2) NZEBs implementation, however, has some limitations, including the negligence of indoor conditions in the analysis, household thermal comfort, and the absence of an energy supply and demand monitoring system. (3) Most researchers advise supplementing facade and window BIPV as solely roofing BIPV will not be able to meet the building's electricity usage. (4) Combining BIPV with building integrated solar thermal (BIST), considering esthetics and geometry, enhances outcomes and helps meet NZEB criteria. (5) BIPV designs should follow standards and learn from successful cases. However, to ascertain the long-term reliability and structural integrity of BIPV systems, a comprehensive study of their potential degradation mechanisms over extended periods is imperative. The review paper aims to examine BIPV applications in-depth, underscoring its pivotal role in attaining a net-zero energy benchmark. [ABSTRACT FROM AUTHOR]

Conventional energy resource problems made power system planners apply more renewable energy sources (RESs) in the power system. RESs have a significant impact on fulfilling the world's energy demand, protecting the environment at least in the exploration phase, and providing energy reliability as well as security for the new generation of power grids. In this regard, wind power generation is considered a promising solution. However, by increasing the share of wind power generation units in the power sector, some challenges, such as voltage problems, transient stability, increasing system losses, and line congestions can occur. Consequently, an alternative solution is required to accelerate wind power units' connections to the grid by preventing the problems caused by the penetration of wind power. In this regard, Flexible Alternating Current Transmission Systems (FACTS) devices can play an important role while they can improve power grid dynamic performance. This paper presents a review of the optimization techniques applied to accelerate the penetration of wind energy by exploiting FACTS devices. The topic identifies the objectives and optimization formulations, as well as schemes and models available in the published literature. This survey gives noteworthy insights to the researchers to cover available solutions in these regards. The literature in the field is summarized in different aspects, such as FACTS technology, objective functions, constraints, optimization methods, planning or operation purposes, and load flow types. At each aspect, a comparison is derived to recognize the most important issues. The result of the review is the finding of future work and contributions which can be done in the field of wind energy integration acceleration using FACTS devices and the output of the paper can be used as a guide for researchers to find a new path for research in this area. [ABSTRACT FROM AUTHOR]

This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system. • An efficient energy storage system is essential for managing intermittent energy supply. • The fuel cell can generate DC power by combining hydrogen with oxygen. • The amount of power generated by a PV panel depends on temperature and solar radiation intensity. • Deterministic rule-based controllers operate based on pre-defined rules. • Energy Management System coordinate the flow of power between different components. [ABSTRACT FROM AUTHOR]

There is a rapid increase in power demand which has led to an increase in the need for smaller grids all over the world. The microgrid is such a small power supply system that consists of loads, distributed energy resources, and energy storage systems. With the development of the internet, the power sector has started the development of the newest type of grids, involving a smart technology called smart grids. Smart grids have got smart integration and advanced storage, along with dynamic optimization of grid operation and resources, digital information and control, distributed resources, demand-side resources, energy efficiency resources, and smart metering systems. The developments in intelligent controllers reflect in power flow management also. This paper gives an idea of how to achieve power flow management through a tariff-based Fuzzy Logic Controller (FLC). The control algorithm used here is the k factor-based Icosϕ algorithm, which decides the amount of power shared by microgrids and the grid based on the load demand. The power forecasting of the microgrid with a solar source is performed using ANN. The regression plot and the error histogram obtained show the accuracy of the ANN controller. The simulation of power flow management of the smart microgrid system is tested and analyzed and the proposed system is compared with other existing research. The hardware implementation of the FLC controller with the Arduino interface which is analogous to real-time measurement is explained in detail to compare the simulation results obtained. [ABSTRACT FROM AUTHOR]

In recent times, the research in sustainable energy resources was integrated with the control approaches of various hybrid renewable energy systems for balancing the electricity generation. The accelerated hybrid energy storage systems and steadily growing energy consumption make the variability and the predictable behavior occur in the renewable energy sources, which requires an energy management system. This paper aims to control hybrid renewable energy systems for power management. The systems consist of photovoltaic (PV) arrays, diesel generators, wind systems with boost converter DC-DC, and inverters. The optimum of the real-time process is less due to prediction errors of multiple renewable sources, which track the output voltage and load current. Model predictive control (MPC) is proposed for problem-solving time operation to address this issue and compensate for the prediction error. The major impact factors, such as optimal split power, stability, reliability of energy, and desired dynamic responses, have been identified by applying the MPC technique. A simulation model has been constructed using MATLAB/Simulink environment to confirm the effectiveness of the MPC technique model. [ABSTRACT FROM AUTHOR]

In recent years, a number of studies have focused on optimizing resource allocation and energy cooperation; however, prior to this time, these two topics were rarely discussed together in the same study. This paper analyzes the topic while keeping in mind both the enormous potential of RE and the difficulties that are associated with resource distribution. We take into consideration the downlink transmission model in millimeter-wave BSs, with each BS being powered by sources of renewable energy (RE), in addition to smart grids, and we optimize for overall system energy efficiency (EE). Within the confines of the constraints imposed by the transmit power of the BSs, the quality of service requirements of the UEs, and the collection energy that is available, an investigation into the problem of resource optimization was carried out with the intention of maximizing the total system energy efficiency (EE) by optimizing user association, power allocation, and energy cooperation. This was done with the intention of maximizing the total system energy efficiency (EE). [ABSTRACT FROM AUTHOR]

The coupling between multiple energy sources such as electricity, gas, and heat is strengthened in an integrated energy system (IES), and this, in turn, improves the operational flexibility of the IES. As an upper-level energy supply system, an IES can play a role as virtual energy storage, which can provide regulating power to smooth out the volatility from large-scale renewable energy generation. The establishment of an aggregating virtual energy storage model for IESs has become an important issue. Under this background, a multi-objective optimization-based adjustable capacity evaluation method is proposed in this paper. Firstly, the mathematical model of an IES considering the coupling of multiple kinds of energy forms is proposed. Then, an aggregating model considering demand response and economic constraints is established to demonstrate the adjustable capacity of the IES. In addition, multi-objective optimization is used to identify parameters in the proposed model, and the normal boundary intersection (NBI) method is used to solve the problem. Finally, a simulation example is provided to verify the effectiveness and feasibility of the proposed method. The external energy demand boundary of the IES can be modeled as virtual energy storage, and the coupling relations of electricity and gas can be presented. Case studies demonstrate that economic constraints narrow the adjustable capacity of the IES while the demand response extends it. [ABSTRACT FROM AUTHOR]

The energy use of residues from agriculture, forestry, and solid waste can foster the transition towards a more renewable energy supply. This paper analyzes the energy potential of the above-mentioned sources for energy applications in Kosovo. The analysis is based on statistical data from different studies and reports, analyzing and calculating them to determine the theoretical and energy biomass potential. Kosovo can increase its self-sufficiency by taking advantage of its rich but under-utilized potential of biomass energy sources. This is a novelty study in this area, considering Kosovo lignite-dominated heat energy and electricity consumption and the available special literature. According to our estimates, the theoretical potential is 6.13 million tons/year, while the biomass energy potential should be around 4.57 million tons/year, including approximately 74.6% of biomass, which can be used for energy needs (heating and electricity). Based on the data and calculations, the available and usable potential shows biomass as an energy source with high potential in Kosovo; its share is very low, but it is reasonable to grow for both environmental and economic reasons. [ABSTRACT FROM AUTHOR]

To overcome its reliance on burning fossil fuels for energy generation and water desalination, Kuwait has pioneered research and cutting-edge projects in renewable energy since the 1980s. This paper examines the power sector in Kuwait and emphasizes the government’s keenness to diversify the country’s electric power supply. It provides a comprehensive overview of Kuwait’s efforts, to emerge as a leading example in the region, fostering collaboration and matchmaking within renewable energy industries. The country’s goal is to meet 15% of the demand for power from renewable energy by 2030, including a reduction in energy use in the building sector by 12% and a decrease in CO2 emissions by 33%. The country’s initiatives revolve around harnessing renewable sources, particularly emphasizing the exploration of solar photovoltaic (PV) systems. Challenges and opportunities are presented to provide information for international institutions, technology companies, designers, researchers, and decision makers, aiming to increase the effectiveness and efficiency of PV project implementation in the country and the region. [ABSTRACT FROM AUTHOR]

Dimensioning approaches for regenerative supply concepts for existing buildings using the example of geothermal energy and photovoltaics For the successful integration of renewable energy sources into the supply concept of existing and new buildings, the required areas on the plot and on the building should be considered at an early stage, because at this point there is still a considerable amount of decision‐making freedom. So far, there are no suitable approaches for the dimensioning of these areas. In this paper, an approach is pursued using dimensioning diagrams, which represent essential ratio parameters. These diagrams were created as an example for a district in Freiberg with typical characteristic values for a multi‐family house, the site‐soil properties, radiation loads, etc. The parameters used for the design of geothermal collectors include the geometry (ratio of circumference to collector area) and the useful area‐related heating energy demand. The optimum is determined by means of an economic efficiency analysis. The application potential of this diagram approach for the first estimation and area dimensioning is large and it can contribute by its low application effort substantially to reducing the hurdles for the use of regenerative energies and to strengthening their economically meaningful application. [ABSTRACT FROM AUTHOR]

In order to improve traditional construction toward zero- or almost zero-energy buildings, there is a demand for more reliable and renewable energy resources. Solar energy is environmentally friendly, abundant, and has a low environmental impact. The integration of solar panels with semitransparent windows is used for electricity generation and sunlight penetration, leading to better energy efficiency and reducing energy consumption. This paper aims to analyze the potential of a novel building-integrated photovoltaic semitransparent window as a resource of sustainable energy to save energy use in the office building. In this study, an advanced multi-physics performance prediction approach for a semitransparent building with integrated photovoltaic windows on office building facades was developed in Bahrain's subtropical desert climate. A parametric study was performed to examine the thermal performance and electrical capacity of semitransparent-integrated photovoltaic solar windows that takes into account the electrical properties, combined radiation and conduction heat transfers, and equivalent heat source methods within solar energy cells. Moreover, a side-by-side comparison study with the reference insulated glass unit investigates the outer and inner surface temperatures. For five design window geometries, 3D-coupled fluid-thermal-electrical multi-physics simulations were run using the COMSOL-coupled solver. The electrical modeling has been developed using MATLAB software, and the energy performance calculation of a sample of a typical commercial building in Manama has been carried out in the ESP-r software environment. The computational results were compared with measurements and manufacturer data. The results obtained illustrate the potential of Xenon-filled double-glazing windows (XDGWs) with integrated PV to save 12% of the energy consumption for cooling purposes in the summer. The results show that the maximum energy produced by solar panels is 248.42 W, and the maximum electrical efficiency of the photovoltaic module is 17.61% at a solar irradiance of 1000 W m−2. The expected annual solar power generated by the building facade using 500 panels is nearly 140,755 kWh. The results suggested that the XDGW with integrated PV outperformed the reference insulated glass unit in terms of thermal insulation, solar heat flux, and U-factor. On the whole, the simulated outer and inside surface temperatures are in good agreement with the measured data. [ABSTRACT FROM AUTHOR]

To promote the green transformation and development of manufacturing enterprises, and aiming at the collaborative optimization of IPPS and multi-source energy supply, this paper proposed a novel multi-verse optimization algorithm. Through the improved operations of embedding the sub-population fusion initialization strategy, the NSGA-II mutation strategy and the disturbance strategy of external files, the algorithm expanded the individual population diversity, developed new search ranges, also improved the optimization performance and the quality of Pareto solutions. The multi-energy consumption comparative experiments verified the multi-source energy supply system can effectively improve the proportion of renewable energy consumption and help the manufacturing enterprises achieve the goal of energy conservation and emission reduction; The algorithms comparison experiments showed the effectiveness, feasibility and competitiveness of the novel multi-verse optimization algorithm for solving the problem of IPPS and multi-source energy supply collaborative optimization for manufacturing enterprises. [ABSTRACT FROM AUTHOR]

The utilization of wind energy has become increasingly popular in the United States and many European countries due to its abundant nature and optimized design. While existing wind turbines are predominantly large-scale and not suitable for standalone or distributed power production, Lubbock County in West Texas offers a diverse range of renewable energy options to meet its energy needs. The region relies heavily on utility-scale wind energy sources to supply power to the Texas Grid, replacing conventional fossil fuel-based systems. Currently, standalone solar PV systems are the preferred choice for renewable energy generation. However, West Texas possesses an ample supply of wind energy that can be harnessed to establish a microgrid and provide standalone power to rural communities. Distributed wind energy offers localized power generation, reducing transmission losses and grid strain, while conventional wind farms require long-distance transmission, leading to efficiency gains. By employing the latest technology and optimizing efficiency, even in low-scale generation, a 6-kilowatt permanent magnet alternator-based distributed wind turbine has been designed. This paper focuses on analyzing the techno-economic aspects of implementing this wind turbine in a real-world scenario, taking into account wind attributes, such as velocity and available power, at the specific location. [ABSTRACT FROM AUTHOR]

The reduction of carbon emissions from the energy industry chain and the coordinated development of the energy supply chain have attracted widespread attention. This paper conducts a systematic review of the existing literature on the energy industry chain and energy supply chain. Based on the analytical results, this paper finds that research gaps exist in the studies of energy consumption structure and resource consumption in energy industry chain. In addition, the studies of coordinated operation mechanisms, risk control and the impact of government policies on the energy supply chain still have some shortcomings. Furthermore, this paper shows that the exploitation and utilization of renewable energy and the sustainable development of the energy industry chain and supply chain have become the major focus of scholars and governments in recent years. Accordingly, this article finally presents the future research prospects and provides managerial insights for policy makers and enterprise managers to accelerate the development of renewable energy resources and to achieve green, low-carbon, coordinated and sustainable development. [ABSTRACT FROM AUTHOR]

Although smart home has received wide attention in recent years, numerous scholars focus more on energy optimization strategy than energy dispatch hardware device (named energy router). Meanwhile, this energy router should have several features, i.e., high renewable energy utilization, energy multi-port and low volume. Thus, this paper designs a nine-port energy router regarding smart home and proposes a multimode hierarchical management strategy for this energy router. First, for the multi-port demand of wind, solar, storage and utilization, this paper presents a nine-port energy router to improve the renewable energy consumption and power supply flexibility. In addition, to reduce the volume of the energy router, a non-isolated AC/DC hybrid topology is constructed through embedding the integrated power electronic converters, which achieves the miniaturization of the energy router. In order to improve the renewable energy utilization rate, the decentralized module control is proposed for the components of energy router to provide the voltage and frequency support for system, and realizes the power sharing of distributed generations (DGs). Furthermore, the power exchange control with three-mode switching is proposed to guarantee the global energy flow balance under complex conditions. Eventually, the feasibility of the energy router is verified by the simulation and experiments. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a new robust distributed approach for the energy management of rural multi‐microgrids communities in Chile. These rural communities are often geographically isolated and have a poor connection to the main electricity grid. Operating them as individual microgrids allows the community to connect to the grid or behave as a stand‐alone system (islanded). Connecting and coordinating the operation of the microgrids can improve the system's robustness to energy and demand uncertainty, as well as reducing the dependency on the main grid. However, this coordination can be challenging because the communication between the different microgrids can sometimes deteriorate, moreover, both load and local generation profiles are challenging to predict. For these reasons, in this paper, a new robust distributed hierarchical Energy Management System (EMS) for coordination of multiple microgrids (multi‐microgrids) is introduced, which uses robust distributed Model Predictive Control (MPC). Distributed optimisation permits improving reliability in the presence of poor or lack of communications between microgrids. To consider the uncertainty associated with renewable energy generation and load consumption, fuzzy prediction interval models are included in the MPC design. The proposed method is compared with robust centralised MPC and deterministic distributed MPC to assess its performance. Simulation results are presented using data representative of a rural community in coastal Chile applied to the robust MPC design. The outcomes of this work demonstrate that the proposed robust distributed EMS can improve the power supply, apply peak shaving, and can successfully operate when there is a loss of communication between microgrids. The use of decreasing fuzzy intervals allows an accurate prediction of both load and renewable energy generation, making the system robust to uncertainty in the available resources. Moreover, results show that in absence of communication, the power supply obtained under different scenarios with the distributed EMS is better than the equivalent centralised EMS. [ABSTRACT FROM AUTHOR]

Two interconnected AC microgrids are proposed based on three renewable energy sources (RESs): wind, solar, and biogas. The wind turbine drives a permanent magnet synchronous generator (PMSG). A solar photovoltaic system (SPVS) with an appropriate inverter was incorporated. The biogas genset (BG) consists of a biogas engine coupled with a synchronous generator. Two interconnected AC microgrids, M1 and M2, were considered for study in this work. The microgrid M2 is connected to a diesel engine (DE) characterized by a continuous power supply. The distribution power loss of the interconnected AC microgrids comprises in line loss. The M1 and M2 losses are modeled as an objective function (OF). The power quality enhancement of the interconnected microgrids will be achieved by minimizing this OF. This research also created a unique frequency control method called virtual inertia control (VIC), which stabilizes the microgrid frequency using an optimal controller. In this paper, the following five controllers are studied: a proportional integral controller (PI), a fractional order PI controller (FOPI), a fuzzy PI controller (FPI), a fuzzy fractional order PI controller (FFOPI), and a VIC based on FFOPI controller. The five controllers were tuned using particle swarm optimization (PSO) to minimize the (OF). The main contribution of this paper is the comprehensive study of the performance of interconnected AC microgrids under step load disturbances, step changes in wind/solar input power, and eventually grid following/forming contingencies as well as the virtual inertia control of renewable energy resources used in the structure of the microgrids. [ABSTRACT FROM AUTHOR]

Renewable energy sources such as wind turbines and photovoltaics are the key to an environmentally friendly energy supply. However, their volatile power output is challenging in regard to supply security. Therefore, flexible energy systems with storage capabilities are crucial for the expansion of renewable energy sources since they allow storing off-demand produced power and reconverting and supplying it on-demand. For this purpose, a novel power plant concept is presented where high-temperature energy storage (HTES) is integrated between the recuperator and the combustor of a conventional micro gas turbine (MGT). It is used to store renewable energy in times of oversupply, which is later used to reduce fuel demand during MGT operation. Hereby, pollutant emissions are reduced significantly, while the power grid is stabilized. This paper presents a numerical process simulation study, aiming to examine the influence of different storage temperatures and load profiles of HTES on the MGT performance (e.g., fuel consumption, efficiency). Furthermore, relevant operating points and their process parameters such as pressures, temperatures, and mass-flow rates are derived. As operation conditions for the combustor are strongly influenced by the HTES, the paper contains a detailed theoretical analysis of the impact on combustor operability and includes an experimental investigation of the first combustor design adapted for the compound and tested under higher inlet temperatures conditions. [ABSTRACT FROM AUTHOR]

Challenges and future perspectives of desalination integration are presented. [Display omitted] • Different optimized models for desalination technologies integration are summarized. • The control strategies of RES-desalination for reducing environmental are discussed. • Impact of desalination process innovation on energy saving and emission reduction. In the present framework, desalination, as an energy-intensive industry, has garnered increased attention due to the imperative need for reducing energy consumption. In this paper, various challenges in the integration and optimal design of desalination processes have been presented. The energy consumption, energy supply method, water production method and improvement measures of various desalination are studied in detail, of which energy consumption is a major aspect. This article summarizes the integration modes of different desalination technologies. Low integration density, inadequate energy utilization and unsystematic theory guidance have been the focus of research. Operational strategies and optimal design methods for the integration of renewable energy and desalination technologies are studied in detail. The integration of renewable energy emerges as a pivotal trend, contributing significantly to the reduction of carbon footprints and costs. Additionally, the significance of recently developed desalination processes, such as pre-treatment process, equipment enhancements and advanced materials have been discussed. Furthermore, various unresolved issues in de integration desalination technologies system have been investigated in the paper along with the possible solutions to address the reported open issues. By exploring the integration of desalination technologies, the paper aims to provide valuable insights for enhancing the efficiency of commercial desalination plants. [ABSTRACT FROM AUTHOR]

Expanding the renewable energy sources usage in power systems will help the government meet its energy policy goals of lowering emissions, ensuring high power supply reliability, and promoting spot markets with high competitivity. However, due to the intermittent nature of these sources, this will necessitate the mitigation of network vulnerabilities. High wind energy penetration in the grid could have an impact on the system frequency, voltage, real and reactive power response, and power quality of the system. The main objective of this paper is to investigate how the integration of wind farms in the Jalan Bani Bu Ali (JBBA) area will affect Oman's main interconnected system (MIS). Results show that the effect is minor on voltage and frequency stability by all disturbances taken into account. [ABSTRACT FROM AUTHOR]

Energy is one of the basic inputs and driving forces for economic and social development modernization. Sustainable energy supply is one of the major challenges in the modern world. Sustainable energy supply can be obtained through alternative energy sources, and efficient energy use is a high priority to optimize the environmental impact. This paper investigates the potential for energy savings involving five end-load equipment in academic institutions. The saving potential is obtained through energy efficiency analysis and feasibility analysis of the solar power generation systems. An energy audit is conducted on end-use consuming equipment (i.e., fans, lights, air conditioning, ICT equipment, etc.) in these five end-load sectors to find out the major energy-consuming equipment, energy consumption, and potential energy savings. The analysis of energy consumption per equipment helps determine the appropriate type of equipment to be upgraded and replaced for energy saving. The feasibility of rooftop solar power generation has been also analysed to integrate into the energy end load. The research findings confirm that laboratory equipment, lighting, and air conditioning are vital to energy consumption in academic buildings. The energy savings, bill savings, and carbon emissions reductions have been estimated based on integrating rooftop solar power generation. The feasibility analysis of onsite energy generation using a hybrid solar system found that the total energy-saving potential and bill savings within five years are 311,131 kWh and RM 113,563, respectively. This value refers to comprehensive energy-saving and bill for all academic buildings involved in this research. [ABSTRACT FROM AUTHOR]

This article offers an overview of distributed generation (DG) in distribution systems (DS). The primary goal of this study is to assess the performance of DGs in DS. Due to the rise in electrical energy consumption, it is anticipated that DG sources would be essential to DS. Future power generating networks have a bright outlook on consideration of DG's potential for utilising alternative energy sources. The quality of power systems is a crucial concern for energy providers and consumers. In order to decrease reliance on fossil fuels for the production of electricity, distributed generations are gaining importance in the energy supply networks in many countries. Distributed generators are small units that generate electricity close to customer sites. These DGs use renewable energy methods such as wind energy, solar energy and geothermal energy. The incorporation of DGs into a conventional power supply system evolves in a number of side effects, including an increase in the number of short circuits, higher power losses, a decrease in the quality of the energy produced, voltage transients, problems with voltage stability, coordination issues regarding voltage regulation and protection, the possibility that system protection will not function correctly, and the fact that there is less residual current input as a result of the DG bidirectional power flows. This review paper discusses the impacts of the penetration of DG into DS and provides various strategies to mitigate these effects. [ABSTRACT FROM AUTHOR]

The problem of energy optimization for Internet of Things (IoT) devices is crucial for two reasons. Firstly, IoT devices powered by renewable energy sources have limited energy resources. Secondly, the aggregate energy requirement for these small and low-powered devices is translated into significant energy consumption. Existing works show that a significant portion of an IoT device's energy is consumed by the radio sub-system. With the emerging sixth generation (6G), energy efficiency is a major design criterion for significantly increasing the IoT network's performance. To solve this issue, this paper focuses on maximizing the energy efficiency of the radio sub-system. In wireless communications, the channel plays a major role in determining energy requirements. Therefore, a mixed-integer nonlinear programming problem is formulated to jointly optimize power allocation, sub-channel allocation, user selection, and the activated remote radio units (RRUs) in a combinatorial approach according to the channel conditions. Although it is an NP-hard problem, the optimization problem is solved through fractional programming properties, converting it into an equivalent tractable and parametric form. The resulting problem is then solved optimally by using the Lagrangian decomposition method and an improved Kuhn–Munkres algorithm. The results show that the proposed technique significantly improves the energy efficiency of IoT systems as compared to the state-of-the-art work. [ABSTRACT FROM AUTHOR]

In the search for sustainable processes and products, eco-friendly policies have been developed over the years, aiming to reduce the environmental impacts as a step toward sustainability. Among the environmental impacts, alternatives to mitigate the greenhouse gas emissions - GHG stand out due to the concerns with climate change. Then, the development and use of renewable resources become relevant. Considering that the supply chains are intense in energy consumption and GHG emissions (since it involves processes related to supply, production, transport, consumption), it becomes relevant to investigate if the management of sustainable supply chain is considering the renewable energies in their processes. Therefore, this paper aims at mapping the role of renewable energies in the context of the sustainable supply chain, analyzing the literature published at Web of Science database - WoS about the subject. The main researchers, organizations, collaboration networks were presented, and the 21 most cited studies were mapped in this paper. The research was carried out with the papers published at WoS until 2019, using VantagePoint software to handle information. The findings show that the research about renewable energy in the context of a sustainable supply chain has been growing, especially since 2010. Moreover, biomass, biofuels and photovoltaic energy were the recurrent sources of renewable energy studied by most cited papers. However, the theme presented itself as new and there is still potential to be explored. [ABSTRACT FROM AUTHOR]

Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS. [ABSTRACT FROM AUTHOR]

Economic, technological, and environmental causes are moving energy toward smart distribution networks. The change from fossil fuels to renewable energy sources is extremely environmentally friendly in both the building and transport sectors. Microgrids could be efficiently used in remote areas utilizing renewable energy resources for supplying different energy demands namely power, heat and cold. This paper presents a mixed-integer linear programming (MILP) model for optimizing planning and sizing decisions in microgrids connected to main grid. Planning decisions the amount of generation of each distributed generation (DG) technology and the amount of power transmission to other nodes. Also, sizing of different DGs including photovoltaic and combined heat and power facilities are performed by the proposed model. According to the results, the model is able to optimize sizing and planning decisions in grid-connected microgrids. [ABSTRACT FROM AUTHOR]

This paper presents and compares three approaches to deal with the uncertain nature of energy supply and demand in the problem of optimal sizing of a stand-alone, reliability-constrained hybrid renewable energy system. The system is composed of wind turbines, photovoltaic solar panels, a battery bank, and a diesel generator. The proposed approaches are: (a) adaptive robust optimization with unmet demand as the (un)-reliability metric, (b) scenario-based robust satisficing, and (c) stochastic-free robust satisficing. A column-and-constraint generation algorithm is developed to solve the adaptive robust optimization problem. Furthermore, the theoretical connection between the proposed approaches is drawn, and their numerical performances are compared, in terms of optimal solution cost and reliability, through computational experimentation on a realistic case study. Numerical results show that both the computational times and the out-of-sample performances of the optimal solutions obtained from the two proposed robust satisficing approaches outperform that of the adaptive robust optimization approach, providing a strong justification for their application • Robust optimal design of a stand-alone hybrid renewable energy system. • Adaptive robust optimization versus robust satisficing optimization. • Optimization under the uncertainty of demand and supply. [ABSTRACT FROM AUTHOR]

In this twenty-first century, energy shortages have become a global issue as energy demand is growing at an astounding rate while the energy supply from fossil fuels is depleting. Thus, the urge to develop sustainable renewable energy to replace fossil fuels is significant to prevent energy shortages. Solar energy is the most promising, accessible, renewable, clean, and sustainable substitute for fossil fuels. Third-generation (3G) emerging solar cell technologies have been popular in the research field as there are many possibilities to be explored. Among the 3G solar cell technologies, perovskite solar cells (PSCs) are the most rapidly developing technology, making them suitable for generating electricity efficiently with low production costs. However, the toxicity of Pb in organic–inorganic metal halide PSCs has inherent shortcomings, which will lead to environmental contamination and public health problems. Therefore, developing a lead-free perovskite solar cell is necessary to ensure human health and a pollution-free environment. This review paper summarized numerous types of Sn-based perovskites with important achievements in experimental-based studies to date. [ABSTRACT FROM AUTHOR]

Nowadays, climate change is a major global societal challenge that significantly increases environmental stress. Most international organizations and policies have promoted initiatives to minimize emissions, reduce fossil fuel dependence and increase renewable energy resource integration into different sectors. An energy transformation towards more renewable systems is thus a priority. Under this scenario, the present paper describes and evaluates an alternative energy conversion matrix-based model to combine sector electrification, power generation units from renewables, and new clean technologies. The proposed green matrix-based model allows analyzing future scenarios, including electricity participation in end-use consumption and electric power generated by renewables – potentially integrated into different sectors –. The proposed model is evaluated in the state of Maine (United States). This case study is focused on decarbonizing both residential heating and transport sector through the integration of large offshore wind power plant. Results and discussion is also included in the paper, providing expected energy demand reductions and decreasing emissions through the integration of renewables. This energy transition integration case study is proposed in three road-maps with different penetration rates and time scales. The proposed green matrix-based model can be also applied to other areas and energy resources, as an alternative way to analyze and estimate renewable integration into different sectors. • Green Electrical Matrix to link electricity supply and end-use for energy transition. • Assesses renewable potential and electrification tech for end uses, e.g., transport. • Applies model to Maine, USA to show reductions in fossil fuels and emissions. • GIS and MCDM for optimal offshore wind location, maximizing electricity generation. • Short, medium, and long-term projections of renewable integration into energy system. [ABSTRACT FROM AUTHOR]

The increasing demand for renewable energy sources has led to the development of HRES that combine multiple sources of renewable energy to provide a reliable and efficient energy supply. However, renewable energy sources typically come with higher costs than conventional energy production methods. Hence, the optimal sizing of HRES is essential to prevent the oversizing of the system while ensuring a reliable supply of load demand, accommodating variations in meteorological conditions and changes in power demand. Numerous research papers addressing the optimal sizing problem are available in the literature. However, none of the mentioned studies take into account the power degradation of all renewable sources. The degradation of renewable sources, such as PV and WT, can have a significant impact on the performance of HRES. The degradation of PV panels can result in reduced efficiency and output, leading to a decrease in the overall energy production of the HRES. Similarly, WT may experience wear and tear over time, leading to reduced performance and output. The reduction in the output of renewables in the standalone system causes an increase in the loss of power supply probability (LPSP). This paper analyzes the optimal sizing of the HRES, considering the degradation of the sources. Further, analysis has also been carried out based on the number of BESS to be added to HRES to meet the derived constraints and their impact on the cost of energy as well. [Display omitted] [ABSTRACT FROM AUTHOR]

The increasing demand for renewable energy sources has led to the development of HRES that combine multiple sources of renewable energy to provide a reliable and efficient energy supply. However, renewable energy sources typically come with higher costs than conventional energy production methods. Hence, the optimal sizing of HRES is essential to prevent the oversizing of the system while ensuring a reliable supply of load demand, accommodating variations in meteorological conditions and changes in power demand. Numerous research papers addressing the optimal sizing problem are available in the literature. However, none of the mentioned studies take into account the power degradation of all renewable sources. The degradation of renewable sources, such as PV and WT, can have a significant impact on the performance of HRES. The degradation of PV panels can result in reduced efficiency and output, leading to a decrease in the overall energy production of the HRES. Similarly, WT may experience wear and tear over time, leading to reduced performance and output. The reduction in the output of renewables in the standalone system causes an increase in the loss of power supply probability (LPSP). This paper analyzes the optimal sizing of the HRES, considering the degradation of the sources. Further, analysis has also been carried out based on the number of BESS to be added to HRES to meet the derived constraints and their impact on the cost of energy as well. [Display omitted] [ABSTRACT FROM AUTHOR]

• This paper proposes the research on dimension reduction for visualization of simplified security region of integrated energy system considering renewable energy access. • The imbalance between energy demand and supply caused by the renewable energy uncertainty is defined as a special N-1 fault. • An interval security region model of integrated energy system is constructed, according to the N-1 safety constraints of equipment and pipeline. • An engineering simplification approach for interval security region model is proposed, in order to quantify the security boundary, security distance, and interval total supply capability. • A dimension reduction observation method based on observation variable optimization is proposed, which can enlarge the volume unaffected by renewable energy uncertainty. This paper proposes the research on dimension reduction for visualization of simplified security region of integrated energy system considering renewable energy access. Reason: Integrated energy system is conducive to achieving low-carbon transition and efficient utilization of energy. As the penetration of renewable energy increases, the security of integrated energy system faces severe challenges. It holds significance for comprehensively studying N-1 security test method in the operation scenario of integrated energy system, the impact of renewable energy on the IES security region model, and the optimal selection for observation variables. Methods: Firstly, a model for interval security region of integrated energy system is constructed, according to the N-1 safety constraints of energy hub key equipment and pipeline. The imbalance between energy demand and supply caused by the renewable energy uncertainty is defined as a special N-1 fault. Then, an engineering simplification approach for interval security region model is proposed, in order to quantify the security boundary, security distance, and interval total supply capability. On the basis, a dimension reduction observation method based on observation variable optimization is proposed, the selection of observation variables help to expand the volume of area unaffected by renewable energy uncertainty. Results: To the existed problem in current research, an example is presented to verify the effectiveness of proposed method, which brings forward N-1 security test method in the operation scenario of integrated energy system, analyzes the impact of renewable energy on the security region model, and realizes the optimal selection for observation variables of simplified security region. Conclusions: Interval security region of integrated energy system can intuitively estimate the security status of operating points and observe the security boundaries. The simplified model can satisfy the needs of calculating precision. Optimal selection of observation variables is necessary, and the volume of area unaffected by renewable energy uncertainty can be effectively increased. [ABSTRACT FROM AUTHOR]

Rural and remote regions of developing economies face a serious scarcity of reliable energy supply. Focus on providing electricity through renewable and off grid energy resources is becoming increasingly popular. Off the grid or decentralized renewable energy typically considers either solar or small hydro power to fill the supply deficit and increase in demand with time is generally ignored. This paper proposes a hybrid technology mix of various renewable energy options for two remote villages located in Darma valley of Uttarakhand state in the Indian Himalayan Region. Since the villages are at an average height of 3500 m amsl, they are inaccessible during winters due to heavy snowfall. Therefore, decentralized energy could be the most cost effective solution to provide electricity. This paper estimates the energy demand of these villages and identifies the most optimum off the grid solutions, and compares it with grid connected electricity supply using hybrid optimization model for electric renewables. Micro hydro energy generation was found to be the most cost effective and techno-economically viable solution. This paper also evaluates the barriers faced by remote Himalayan villages so as to achieve reliable application of the results of this study. [ABSTRACT FROM AUTHOR]

The complex energy conversion and the volatility of renewable energy/load bring great challenges to the operation of the park‐level integrated energy system (PIES). To overcome this challenge, this paper proposes a multi‐timescale flexible dispatching method to fully exploit the flexibility of PIES in the energy cascade utilization mode. The cascade utilization model for energy flow is firstly established to analyse the coupling and complementary of heterogeneous energy. On this basis, the supply‐demand general equations of multi‐energy flexibility are proposed, which accurately quantify the ability to cope with uncertainty through mutual flexibility. Through coordinated complementation and mutual exchange of multi‐grade flexibility, the system realizes the suppression of random power fluctuations. The scheduling model includes day‐ahead dispatch and intraday multi‐time scale dispatch, which can satisfy the adjustment speed requirements of different energy. Numerical results demonstrate that the proposed method effectively enhances the flexibility and economy of system operation. The flexible demand for energy of all grades can be satisfied. Compared with the flexible dispatch in the triple energy supply structure, the operating cost is reduced by 9.07%. [ABSTRACT FROM AUTHOR]

Islands are facing significant challenges in meeting their energy needs in a sustainable, affordable, and reliable way. Traditionally, the primary source of electricity on the islands has been imported diesel fuel, with high financial costs for most utilities. In this context, even replacing part of the traditional production with renewable energy source can reduce costs and improve the quality of life of islanders. However, integrating large amounts of renewable energy production into existing grids introduces many concerns regarding feasibility, economic analysis, and technical implementation. From this point of view, machine learning and deep learning techniques are efficient tools to mitigate these problems. Their potential results are beneficial considering isolated grids of small islands which are not connected to the national grid. In this paper, a study of the Italian island of Ponza is carried out. The isolation leads to several challenges, such as the high cost related to the transport, installation, and maintenance of renewable energy sources in a small area with several constraints and their intermittent power production, which requires the use of storage systems for dispatching purposes. The proposed study aims to identify future developments of the electricity grid by considering the deployment of both renewable energy sources and energy storage systems. Furthermore, future scenarios are depicted through the use of autoregressive and deep learning techniques to give an idea about the economic costs of both energy demand and supply. [ABSTRACT FROM AUTHOR]

The introduction of the new round of electricity reform policies has made the electricity sales companies' trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China's current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market. [ABSTRACT FROM AUTHOR]

Different renewable energy resources and energy demands between parks lead to waste of resources and frequent interactions between the regional distribution grid and the larger grid. Hence, an optimal dispatching scheme of the regional integrated energy system group (RIESG), which combines the power-to-gas (P2G) and inter-park electric energy mutual aid, is proposed in this paper to solve this problem. Firstly, for the park integrated energy system (PIES) with various structures, the coupling matrix is used to describe the input-output relationship and coupling form of multiple energy sources in the energy-hub (EH), which linearizes the complex multi-energy coupled system and is more conducive to the solution of the model. Secondly, the electrical coupling relationship of the system is improved by adding P2G to enhance the system's ability to consume renewable energy. Moreover, the installation cost of P2G is introduced to comprehensively consider the impact of the economic efficiency on the system. Finally, to minimize the network loss of energy flow, the optimal dispatching model of RIESG with P2G conversion is constructed through the electric energy mutual aid among the parks. The simulation shows that compared with the independent operation of each park's integrated energy system (IES), the proposed optimal dispatching strategy of RIESG achieves the mutual benefit of electric energy among park groups, reduces the dependency on the large power grid, and effectively improves the economy of system groups. In this condition, the renewable energy consumption rate reaches 99.59%, the utilization rate of P2G increases to 94.28%, and the total system cost is reduced by 34.83%. [ABSTRACT FROM AUTHOR]

Summary: The need to increase the share of renewable energy supply in buildings has been a subject of concern for many authors. Renewable energies can offset building electrical and thermal energy loads, thus reducing constrains on national grid networks. The aim of this paper is to construct, model and optimize a hybrid renewable energy supply system under transient conditions. The supply system consists of solar‐PV panels and vertical axis wind turbines, while batteries are used for energy storage. TRNSYS software is used to model the energy demand of an office building that operates under the average standard building as specified in EnergyPlus software. In order to determine the optimal size of the energy supply system an Artificial Neural Network (ANN) combined with a Sobol algorithm are employed. Two objective functions are developed to: (a) minimize the cost of purchasing solar‐PV panels and wind turbines, and (b) minimize the electricity required from the national grid network. The simulation and optimization results show that the best condition is achieved with 461 panels and one vertical axis wind turbine. At this best condition, the amount of electricity required from the national grid network is 5.55 MWh/year, and this will cost 2.4 $/h. Moreover, 3% of electricity will be obtained from the grid, 31% from batteries and 66% are supplied directly through panels and turbines. [ABSTRACT FROM AUTHOR]

In modern power systems, the reliability of energy supplies is a real challenge for the operators. The emergence of renewable energy resources, along with multi-career users, requires multi-career systems. In this regard, the energy hub (EH) as an integrated system can be used to increase the reliability of the system. The power-to-gas (P2G) and P2G storage are two practical technologies to achieve high efficiency in energy systems. In this paper, the contribution is optimal scheduling of stochastic problem in EH system amalgamated with CHP unit, P2G storage, thermal storage, boiler, wind power, and electrical storage to supply the heat, gas, and power loads by regarding demand response program (DRP). For the electrical loads, the load shifting strategy is considered to minimize the operational cost of the EH system. In order to manage related uncertainties about electricity price, wind power, and electrical loads, the downside risk constraint (DRC) method is applied to investigate the EH system function. According to the obtained results, by increasing approximately 2.8% of the operational cost, the risk level can be reduced remarkably. And also, almost 10% of the energy shifted from peak hours to the off-peak time after DRP is applied. • Optimization of power, heat and gas energy consumption in an energy hub. • Energy hub system is integrated with power-to-gas storage. • All uncertainty parameter are modeled via scenario based stochastic programming. • Downside risk constrained approach is proposed for risk modeling in energy hub. • Risk-averse and risk-neutral strategies are compared with each other. [ABSTRACT FROM AUTHOR]

Renewable-energy-based microgrids (MGs) are being advocated around the world in response to increasing energy demand, high levels of greenhouse gas (GHG) emissions, energy losses, and the depletion of conventional energy resources. However, the high investment cost of the MGs besides the low selling price of the energy to the main grid are two main challenges to realize the MGs in developing countries such as Iran. For this reason, the government should define some incentive policies to attract investor attention to MGs. This paper aims to develop a framework for the optimal planning of a renewable energy-based MG considering the incentive policies. To investigate the effect of the incentive policies on the planning formulation, three different policies are introduced in a pilot system in Iran. The minimum penetration rates of the RESs in the MG to receive the government incentive are defined as 20% and 40% in two different scenarios. The results show that the proposed incentive policies reduce the MG's total net present cost (NPC) and the amount of carbon dioxide (CO2) emissions. The maximum NPC and CO2 reduction in comparison with the base case (with incentive policies) are 22.87% and 56.13%, respectively. The simulations are conducted using the hybrid optimization model for electric renewables (HOMER) software. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RES) are currently the main alternative to fossil fuels and are also seen as an important contributor to slowing down the dangerous climate change on our planet. Energy supplied from renewable sources can reduce the consumption of primary raw materials and reduce emissions of harmful substances that enter the atmosphere in the process of producing electricity and heat, having a negative impact on the environment. This paper provides a multivariate comparative analysis of EU countries in terms of the use of renewable energy. The empirical research used seven variables defining the complex phenomenon under study, collected for 27 EU countries between 2011 and 2020. The research method used was the dynamic version of the non-model method, with a normalisation method based on zero unitarisation. The results of the study confirm that there was a positive change in the use of renewable energy in most EU countries between 2011 and 2020. High levels of renewable energy use were displayed by the Scandinavian countries, Sweden, Finland, and Denmark. In contrast, the least renewable energy use was seen in Poland, Hungary, and Slovakia. [ABSTRACT FROM AUTHOR]

Renewable energy resources have gained considerable attention in recent years due to their efficiency and economic benefits. Their proportion of total energy use continues to grow over time. Photovoltaic (PV) cell and wind energy generation are the least-expensive new energy sources in most countries. Renewable energy technologies significantly contribute to climate mitigation and provide economic benefits. Apart from these advantages, renewable energy sources, particularly solar energy, have drawbacks, for instance restricted energy supply, reliance on weather conditions, and being affected by several kinds of faults, which cause a high power loss. Usually, the local PV plants are small in size, and it is easy to trace any fault and defect; however, there are many PV cells in the grid-connected PV system where it is difficult to find a fault. Keeping in view the aforedescribed facts, this paper presents an intelligent model to detect faults in the PV panels. The proposed model utilizes the Convolutional Neural Network (CNN), which is trained on historic data. The dataset was preprocessed before being fed to the CNN. The dataset contained different parameters, such as current, voltage, temperature, and irradiance, for five different classes. The simulation results showed that the proposed CNN model achieved a training accuracy of 97.64% and a testing accuracy of 95.20%, which are much better than the previous research performed on this dataset. [ABSTRACT FROM AUTHOR]