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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 rapid development of renewable energy and the increasing maturity of energy storage technology, microgrids are quickly becoming popular worldwide. The stochastic scheduling problem of microgrids can increase operational costs and resource wastage. In order to reduce operational costs and optimize resource utilization efficiency, the real-time scheduling of microgrids becomes particularly important. After collecting extensive data, reinforcement learning (RL) can provide good strategies. However, it cannot make quick and rational decisions in different environments. As a method with generalization ability, meta-learning can compensate for this deficiency. Therefore, this paper introduces a microgrid scheduling strategy based on RL and meta-learning. This method can quickly adapt to different environments with a small amount of training data, enabling rapid energy scheduling policy generation in the early stages of microgrid operation. This paper first establishes a microgrid model, including components such as energy storage, load, and distributed generation (DG). Then, we use a meta-reinforcement learning framework to train the initial scheduling strategy, considering the various operational constraints of the microgrid. The experimental results show that the MAML-based RL strategy has advantages in improving energy utilization and reducing operational costs in the early stages of microgrid operation. This research provides a new intelligent solution for microgrids' efficient, stable, and economical operation in their initial stages. [ABSTRACT FROM AUTHOR]

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy sources in virtual power plants (VPP), this paper proposes a framework for collaborative utilization of pumped storage–carbon capture–power-to-gas (P2G) technologies. It also constructs a multi-time scale low carbon economic dispatch model for VPP to minimize the internal resource operation cost of VPP in each time period. During the intraday scheduling stage, the day-ahead scheduling results as the planned output and the energy flow is then dynamically corrected at a short-term resolution in the framework. This allows for the exploration of the low-carbon potential of each aggregation unit within the virtual power plant. The results of the simulation indicate that the strategy and model proposed in this paper can effectively encourage the consumption of renewable energy sources, promote the low-carbon operation of power system power, and serve as a valuable reference for the low-carbon economic operation of the power system. [ABSTRACT FROM AUTHOR]

Under the background of green and low‐carbon transformation of industrial high‐energy‐consuming parks, in order to realize the coordinated development planning of energy and transportation under different peaking capacity requirements, this paper proposes a collaborative optimization model of industrial high‐energy‐consuming parks under green and low‐carbon. Firstly, by studying the energy balance mechanism between industrial load and new energy, an energy topology prior model of energy interaction in the next generation of industrial new energy power grid is constructed. Then, based on the probability characteristics of the equilibrium state of different regions in the high‐energy‐consuming industrial zone, combined with the prior knowledge of industrial load and low‐carbon power system, a collaborative development planning model of high‐energy‐consuming industrial parks is constructed. Finally, the proposed model is simulated. From the simulation results the authors can see the dynamic division model and solution algorithm of energy balance region established in this paper can effectively improve the energy balance ability of power grid, reduce peak shaving demand and use more renewable energy. [ABSTRACT FROM AUTHOR]

Human activities overwhelm our environment with CO2 and other global warming issues. The current electricity landscape necessitates a superior, continuous power supply and addressing such environmental concerns. These issues can be resolved by incorporating renewable energy sources (RESs) into the utility grid. Thus, this paper presents an optimized hybrid fuzzy logic self-tuning PID controller to control the automatic generation control (AGC) of various renewable sources. This controller regulates the frequency deviations of the power system and governs the change in the tie-line load of a multi-area hybrid energy system composed of wind, biomass, and photovoltaic energy sources. MATLAB Simulink software was applied to design and test the system. The PID controller has been tuned using four algorithms, namely, genetic algorithm (GA), pattern search (PS), simulated annealing (SA), and particle swarm optimization (PSO), and we compared the results with the proposed novel optimized PID controller (GA-fuzzy logic self-tuning technique) to validate it. The results show the superiority of the proposed hybrid GA-fuzzy logic self-tuning algorithm over the other algorithms in bringing the power system back to its regular operation. The paper also proposes an operation strategy to lower the utilization of biomass energy in the presence of other renewable energy sources. [ABSTRACT FROM AUTHOR]

This study explored the association between renewable energy uptake and digitalization in the sector by reviewing relevant literature (published 2010–2022), with the aim of identifying the existing utilization of digital technologies within the sector, challenges to adoption, and future prospects. Different search engines (SCOPUS, Web of Science, and Google Scholar) were used to locate relevant papers and documents. The results revealed the high significance of digital technologies in supporting the renewable energy sector, with high costs and security risks representing the key challenges. Most papers reviewed had a positive outlook, but recommended further research and development for effective energy transition and resilient infrastructure. The current drivers of the integration of digital technologies to support the diffusion of renewable energy sources appear to extend beyond energy demand and involve many aspects of sustainability and sustainable development. Compared with previous reviews, this work has unique scope and novelty since it considers the bigger picture of the coupling between digitalization and the renewable energy sector, with a greater focus on critical areas in these two interconnected bodies that need to be addressed. The relatively small sample of relevant papers (69 from 836 hits) located in the literature review confirms the need for more research covering the subject in greater depth. [ABSTRACT FROM AUTHOR]

In the European Union, increasing attention is already being paid not only to the development of renewable energy sources, but also to the establishment of solutions to achieve local energy self-sufficiency while increasing the role of citizens in managing the energy they generate. This approach is expected both to have a positive impact on the environment and the reduction of greenhouse gas emissions, and to enhance energy security—both in economic and civic terms by, i.a., combating energy poverty. The development of local energy communities promoted in the EU is supported i.a. by energy cooperatives. These contribute to the efficient harnessing of renewable energy potential in rural and urban-rural areas, and have been developing in Poland for several years now. In their previous studies, the authors of this research paper attempted to verify the generation (number, type and capacity of installed sources) and consumption (energy demand) configurations in which an energy cooperative would be a viable solution for prosumers who might establish it. However, over the past few years, the conditions for prosumers and the method of their accounting with the electricity seller have changed radically in Poland (shift from net metering to net billing). This situation has opened up space for further research and encouraged the authors to revisit the problem of analyzing the viability of establishing energy cooperatives in relation to the rules of operation of individual prosumers. This research was carried out for three scenarios, and the horizon of the analyses conducted and described extends to 2045. The comparative analysis included energy consumers without their own generation sources, prosumers with a photovoltaic generation installation covered by the net billing model, as well as a scenario involving prosumers' cooperation within an energy cooperative, which by law is settled in the net metering model. Conclusions from the research and simulations made it possible to confirm the claim that, despite changes in the rules of prosumer billing, developing energy independence in the energy community formula results in a significant reduction in the cost of purchasing electricity (even several times lower purchase costs in the timeframe analyzed) and can lead to a reduction in the payback time of investments in generation sources even by a factor of two. The results presented in this research paper open up space for further research. The outcomes allow us to assume that energy cooperatives—in the organizational and institutional model in Poland—are a good tool for reducing the phenomenon of energy poverty on a local scale. [ABSTRACT FROM AUTHOR]

The deregulation of the electricity market has been accompanied by the growing utilization of unpredictable renewable energy sources (RESs) such as solar, wind, and hydropower plants. Additionally, advancements in energy storage technologies and new energy demands have further contributed to this trend. As a result, the planning and operation of power systems are now surrounded by a higher level of uncertainty. In order to ensure the proper operation of power systems integrated with RESs, modern power systems are equipped with specific vital tools such as optimal power flow (OPF), which regulates generation and demand to achieve specific objectives. Hence, this paper conducts a comprehensive review of recently published research articles focusing on various solution strategies to address OPF problems in the presence of stochastic RESs and power demand. The review encompasses diverse solution methodologies, objective functions, constraints, and distinct techniques to simulate the stochastic behavior of RESs and dynamic loads. Additionally, the paper explores fundamental challenges, identifies critical research gaps, and highlights unexplored areas pertaining to optimal power system operation in the future. This review is essential for system operators who need to assess and pre-plan flexibility competency for their power systems to ensure practical and cost-effective operation under high RESs penetration. [ABSTRACT FROM AUTHOR]

The global energy crisis, which began in 2021 due to the extraordinary economic recovery after the pandemic and intensified after Russia's invasion of Ukraine in February 2022, has changed the conditions of energy management, paying more attention to energy efficiency. Natural gas prices have reached record levels and, consequently, so have electricity prices in some markets. Oil prices have reached their highest level since 2008. Higher energy prices have contributed to sharply increased inflation. Households are again becoming interested in buying coal as a source of heat. High energy and gas prices have pushed many families into poverty and forced some factories to cut production or even close. They have also slowed economic growth to the point where some countries are heading for a serious recession. Paradoxically, the negative effects of the energy crisis may accelerate the introduction of cleaner, sustainable, renewable energy such as wind and solar energy. The energy crisis is comparable to the oil crisis of the 1970s, when it contributed to significant advances in energy efficiency. The current crisis has highlighted the importance of investments in renewable energy resources and initiated the process of integrating regional markets, developing energy efficiency and promoting renewable energies. The aim of this article is to comprehensively explore the complex relationship between energy awareness, consumption patterns, and energy efficiency, with a focus on both individual consumers and industries, during the global energy crisis. This paper is based on a literature review, overarching policy documents, energy reports, and other secondary documents. The primary research method was the systematic literature review method, based on which the impact of the global energy crisis on energy efficiency was evaluated. This study emphasizes the diverse influences on energy awareness, ranging from economic factors to consumer preferences and environmental consciousness. The findings of the paper underscore the significant responsibility of industries in contributing to energy-saving efforts and the active role of consumers in the energy market. The responsibility of industries in contributing to energy efficiency is highlighted, with a call for a comprehensive approach that integrates energy-saving criteria into product development and corporate social responsibility. [ABSTRACT FROM AUTHOR]

Due to the widespread use of multi-generation systems utilizing renewable energy sources and the growing global demand for such systems from both economic and environmental considerations, numerous researchers have focused on the design and evaluation of their performance. To this end, this research presents a biomass-based multi-generation system with an innovative and practical design that can generate electricity, heat, and hydrogen. This system includes a modified gas turbine cycle, a supercritical CO 2 (SCO 2) cycle, a transcritical CO 2 (TCO 2) cycle, a proton exchange membrane (PEM) electrolyzer, and a PEM fuel cell unit. This study aims to evaluate the impact of various biomass sources (paper, wood, paddy husk, and municipal solid waste) on the system performance. The proposed system has been analyzed using the first and second laws of thermodynamics. This system uses the maximum capacity to produce power, heat and hydrogen. A fuel cell unit has been used to consume hydrogen and generate more electricity. In the basic mode, the system has energy and exergy efficiencies of 47.89% and 32.26%, respectively, and can produce 2.74 kg/h of hydrogen. The biomass fuel consumption rate within the system is 0.055 kg/s. The overall exergy destruction of the system amounts to 1240 kW, with the biomass boiler and the condenser being the components that experience the greatest exergy destruction, registering values of 535.5 kW and 432.3 kW, respectively. Notably, employing municipal waste as biomass increases the system's exergy efficiency to 33.16%. • To investigate a biomass-driven system for producing power, hydrogen, and heating. • To evaluate the impact of various biomass sources on the system performance. • To use PEME for hydrogen and PEMFC for power and heat production. [ABSTRACT FROM AUTHOR]

There is a great desire to integrate multiple energy systems by forming low-carbon energy hubs. Among various energy platforms, the integration of power and gas networks via Power-to-Gas (PtG) technologies is introduced as a promising solution to enhance the flexibility of power grids and facilitate seamless adoption for high penetration levels of renewable energy resources. In addition, the production of green hydrogen from waste/inexpensive clean electricity has recently been identified as a potential means for large-scale energy storage, deployment of hydrogen mobility, and decarbonization of several processes that utilize hydrogen. As integrated hydrogen-based energy hubs (H 2 Hubs) attract more attention for widespread deployment, the security of such new platforms against various cyberattacks is also becoming a critical topic for investigation. This paper proposes a new data estimation technique, developed and integrated with H 2 Hubs scheduling models, for real-time optimal adaptive collection and organization of the system operating parameters for cybersecurity assessment. A new formulation is presented for the adaptive formation of a newly proposed concept, referred to as the system feasibility area , via real-time acquisition of the system operating information. The created feasibility areas are utilized for real-time post-occurrence detection of the bad scheduling data that is invisible to the existing cybersecurity layers. Numerical studies are conducted to demonstrate the efficacy and feasibility of the proposed model. The results demonstrate that the historical data can be adaptively collected in real time and successfully utilized to create feasibility areas to categorize the system operating points. • An optimal scheduling model is proposed for hydrogen-based energy hubs (H 2 Hubs). • A new data estimation method is developed and integrated with the scheduling model. • A new formulation is given for the adaptive creation of the feasibility area. • Simulation case studies are presented and discussed. [ABSTRACT FROM AUTHOR]

The rapid growth of global energy consumption and the increasing demand for sustainable and renewable energy sources have urged vast research into harnessing energy from various sources. Among them, the most promising approaches are nanogenerators (NGs) and solar cells (SCs), which independently offer innovative solutions for energy harvesting. This review paper presents a comprehensive analysis of the integration of NGs and SCs, exploring advanced hybrid structures and their diverse applications. First, an overview of the principles and working mechanisms of NGs and SCs is provided for seamless hybrid integrations. Then, various design strategies are discussed, such as piezoelectric and triboelectric NGs with different types of SCs. Finally, a wide range of applications are explored that benefit from the synergistic integration of NGs and SCs, including self‐powered electronics, wearable devices, environmental monitoring, and wireless sensor networks. The potential for these hybrid systems is highlighted to address real‐world energy needs and contribute to developing sustainable and self‐sufficient technologies. In conclusion, this review provides valuable insights into the state‐of‐the‐art developments in NGs and SCs integration, shedding light on advanced hybrid structures and their diverse applications. [ABSTRACT FROM AUTHOR]

The shared energy storage system is recognized as a promising business model for the coordinated operation of integrated energy systems (IES) to improve the utilization of energy storage and the consumption of renewable energy. As the hydrogen energy gradually receives more attention, this paper constructs the structure of a hybrid hydrogen energy storage system shared by an IES alliance in a dynamic pricing mode. A bi-level optimization model for the shared hybrid hydrogen energy storage system (SHHESS) is proposed to optimize the capacity configuration decisions and the pricing strategy jointly. The upper level determines the capacity and dynamic price of SHHESS with maximum profits and the lower level obtains the optimal operation of the IES alliance minimizing the total operation costs. The proposed model is solved by an improved PSO-GA algorithm and CPLEX solver. Finally, numerical tests are conducted in different scenarios. The results show that the hybrid energy storage system improves the daily profits of SHHESS by 70.3% and 5.44%, and reduces the renewable energy curtailment by 80.93% and 48.92% respectively compared to the battery-only and hydrogen-only systems. Additionally, the daily operation cost of the IES alliance is 35.2% lower than the individual operation scenario. The proposed model confirms the feasibility and superiority of the hybrid hydrogen energy storage system in a sharing business mode. • Design an interactive structure of a shared hybrid hydrogen energy storage system. • Propose a bi-level planning optimization framework for shared hybrid hydrogen energy storage. • The dynamic price of energy storage sharing service is optimized. • Determine the optimal operation strategy of the integrated energy system alliance. • Propose a hybrid method combining an improved PSO-GA and CPLEX optimizer. [ABSTRACT FROM AUTHOR]

Year after year, there are alarming data concerning the excessive release of greenhouse gases into the atmosphere, especially CO2 from the burning of fossil fuels. In this context, the development of renewable energy sources has evolved considerably, mainly due to the incentive use of biofuels, such as bioethanol. The second-generation bioethanol production from lignocellulosic biomasses has interesting potential to meet this energy demand. The Eucalyptus tree stands as a primary example of cultivated hardwoods, owing to its lignocellulosic structure and the biomass residues generated during its processing, where these attributes make it a significant candidate for the production of fuels. The industrial potential of these materials can be explored in the fractionation of their components to reduce their recalcitrance due to the triad formed by cellulose, hemicellulose, and lignin, for further processing and obtaining the products of interest. This paper comprehensively gathers the current technological progress employed for processing Eucalyptus wood biomasses for second-generation bioethanol production. Discussion regarding their chemical composition, the main forms of pretreatments that are being applied, and ways to minimize the generation of fermentative inhibitors during these processes is addressed. Finally, recent researches focused on Eucalyptus biomass-based bioethanol production and techno-economic considerations are discussed. The feasibility of the process is closely tied to the comprehensive utilization of products derived from this biomass. While production appears relatively effective at the laboratory scale, further research is required to develop a cost-effective process that fully harnesses the potential of the biomass. [ABSTRACT FROM AUTHOR]

Since the International Maritime Organization has paved the way towards zero emissions, more frequent applications of transition fuels in newly constructed ships have been observed. Fuels such as LNG or methanol are characterised by lower emissions when burned in engines. In order to diminish fuel consumption, and hence the rate of emission, support for the performance of a ship's engines with energy from renewable sources such as photovoltaic (PV) installations is increasingly common. The efficiency of PV panels decreases with an increase in temperature, and it is therefore important to cool them. However, the cooling systems for PV panels impose additional financial outlays as well as a higher demand for electric power, which is needed to run the circulating pumps. A natural cooling process can occur in some vessels via high sea waves, when the ship's decks are flooded by outboard water, although such cooling has an accidental and periodic character, as it results from weather conditions. Despite this, its potential demands a closer examination. This paper presents experimental research carried out with an experimental setup that allowed us to simulate the process of flooding of a PV panel with water waves of various frequencies, resulting from choppy periods at sea. Depending on the weather conditions and the character of flooding, our results indicate that an increase in the power of the PV module of about 18% is obtainable. Our research shows that when the intervals between flooding are longer, the periodic character of the temperature changes obtained by flooding the front surface of a PV panel with water is more distinctive. [ABSTRACT FROM AUTHOR]

This paper proposes the Hybrid desalination and power generation through parabolic trough collectors. This study aims to examine the feasibility, performance optimization, and economic viability of power-generation plant and hybrid-desalination using multi-stage flash (MSF) and reverse osmosis (RO) technologies assessed by using the parabolic trough collectors (PTC). The objective is to discover the posibilities of this innovative approach in addressing water scarcity and clean energy demands. The studies usually focus on several key aspects. Firstly, it resolves the technical feasibility of integrating MSF and RO technologies with parabolic-trough-collectors to optimize energy efficiency and freshwater production. This involves evaluating the system design, heat transfer mechanisms, and operational parameters.Secondly, performance optimization is a key area of investigation. By optimizing these parameters the aim is to maximize freshwater production while minimizing energy consumption. Thirdly, the economic viability of the hybrid plant will be assessed. This involves considering capital investment, conducting a comprehensive cost analysis, maintenance costs, and operational expenses. The study also evaluates the potential for revenue generation through the sale of excess electricity produced by the system. The potential outcomes of this research include demonstrating the technical-feasibility as well as economic-viability of the hybrid desalination and power generation plant. The findings may indicate that this approach can effectively address water scarcity challenges while contributing to clean energy production. The study may also highlight the environmental benefits of integrating renewable energy sources (RESs) and decreasing greenhouse gas emissions compared to traditional desalination methods.The proposed method is executed in MATLAB platform and compared to various existing approaches. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RES) are currently being substantially integrated into the power grid because of the recent liberalization of the energy market and associated benefits to both the environment and the economy. A significant amount of renewable energy sources are stochastic and weather dependent, being integrated into the power system that causes a mismatch between the generation of power and the load demand, which creates major issues like variations in frequency and power transmission between the regions. So it is necessary to maintain the frequency and tie-line power variations within a defined range. This is known as automatic generation control (AGC) or load frequency control (LFC). This paper uses brown bear optimization algorithm (BOA) to tune the PID and cascaded PI-PDN controllers for LFC of the renewable integrated two-area power system. The ITAE objective function is utilized to obtain optimal gains of the PID controller. The performance of LFC with BOA-tuned PID controller is compared with other optimization techniques named grey wolf optimization technique (GWO) and particle swarm optimization (PSO) on a RES integrated two-area power system under various scenarios. Further, the effectiveness of the BOA is verified by comparing performance of the PID and cascaded PI-PDN controllers. According to simulation results, BOA offers superior performance in comparison with the GWO and PSO technique. [ABSTRACT FROM AUTHOR]

The strategic objective of world climate policy is the decarbonization of industries, aiming to achieve "net-zero" emissions by 2050, as outlined in the European Green Deal and the Paris Agreement. This transition entails increasing the utilization of renewable energy sources (RES) in industrial energy consumption, thereby transforming economies from reliance on fossil fuels to sustainable alternatives. However, this shift poses a significant challenge for many EU countries, with varying degrees of success in adaptation. This paper investigates the process of decarbonizing industries by analyzing trends in the adoption of RES in EU countries and evaluating their progress toward climate targets. Utilizing time series analysis of production, total energy usage, and the proportion of renewables in industrial energy consumption, the study compares two groups of countries: longstanding EU members and newer additions. The aim is to forecast the trajectory of RES integration in industry and assess the feasibility of meeting the targets outlined in the European Green Deal. The findings reveal a considerable gap between the set targets and projected outcomes, with only a few countries expected to meet the EU's 2030 goals. This is highlighted by disparities in RES shares across member states, ranging from 0.0% to 53.8% in 2022. Despite notable increases in the absolute use of renewable energy, particularly in central and eastern European nations, substantial challenges persist in aligning industrial sectors with EU decarbonization objectives. [ABSTRACT FROM AUTHOR]

As the demand for sustainable energy solutions grows, there is a critical requirement for continuous innovation to optimize the performance and safety of renewable energy systems (RESs). Closed-loop digital twins (CLDTs)—synchronized virtual replicas embedded with real-time data and control loops to mirror the behavior of physical systems—have emerged as a promising tool for achieving this goal. This paper presents a systematic literature review on the application of digital twin (DT) technology in the context of RESs with an emphasis on the impact of DTs on the efficiency, performance, and safety assurance of RESs. It explores the concept of CLDTs, highlighting their key functionalities and potential benefits for various renewable energy technologies. However, their effective implementation requires a structured approach to integrate observation, orientation, decision, and action (OODA) processes. This study presents a novel OODA framework specifically designed for CLDTs to systematically identify and manage their key components. These components include real-time monitoring, decision-making, and actuation. The comparison is carried out against the capabilities of DT utilizing the OODA framework. By analyzing the current literature, this review explores how DT empowers RESs with enhanced efficiency, reduced risks, and improved safety assurance. [ABSTRACT FROM AUTHOR]

The measures needed to limit global warming pose a particular challenge to current fossil fuel exporters, who must not only decarbonise their local energy systems, but also compensate for the expected decline in fossil fuel revenues. One possibility is seen in the export of green hydrogen. Using Algeria as a case study, this paper analyses how different levels of ambition in hydrogen exports, energy efficiency and fuel switching affect the cost-optimal expansion of the power sector for a given overall emissions reduction path. Despite falling costs for photovoltaics and wind turbines, the results indicate that in countries with very low natural gas prices, such as Algeria, a fully renewable electricity system by 2050 is unlikely without appropriate policy measures. The expansion of renewable energy should therefore start early, given the high annual growth rates required, which will be reinforced by additional green hydrogen exports. In parallel, energy efficiency is a key factor as it directly mitigates CO2 emissions from fossil fuels and reduces domestic electricity demand, which could instead be used for hydrogen production. Integrating electrolysers into the power system could potentially help to reduce specific costs through load shifting. Overall, it seems advisable to analyse hydrogen exports together with local decarbonisation in order to better understand their interactions and to reduce emissions as efficiently as possible. These results and the methodology could be transferred to other countries that want to become green hydrogen exporters in the future and are therefore a useful addition for researchers and policy makers. • The required strong capacity expansion for PV and wind is challenging, but feasible. • "Energy efficiency first" benefits both the local energy transition and H2 exports. • Fully renewable power systems require a suitable political framework. • Higher hydrogen exports might help to reduce the specific power system cost. • Fossil capacity expansion must be stopped to avoid lock-ins and higher future costs. [ABSTRACT FROM AUTHOR]

To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology. [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 challenges posed by climate change and global warming loom large, necessitating a critical initial step towards the long-term growth and the enhancement of both environmental and operational efficiency. Within the energy sector, renewable energy sources are gaining increasing prominence. Consequently, traditional oil and gas companies (OGC) are undergoing a gradual transformation into comprehensive energy corporations, aligning themselves with energy transition policies. This paper examines two types of efficiency measures—operational and environmental—for the 20 largest OGC during the period of 2010–2019. Secondly, this research aims to explore the effect of the global energy transition on both environmental and operational efficiency. Based on three estimation methods, two estimation steps are used in this research. In the first step, the True Fixed Effect (TFE) model and the Battese and coelli (1995) SFA model are applied to evaluate, measure and compare the environmental and operational efficiency scores. In the second step, the TFE model and GMM approach for the dynamic panel data model are used to explore, evaluate and verify the effect of global energy transition on the environmental and operational efficiency of the largest 20 OGC in the world. The results reveal that the average operational efficiency of major OGC measured using the BC.95 model and TFE model is 66% and 85%, respectively, and the overall average level of environmental efficiency for OGC over a 10-year period is 31% (based to B.C.95 model) and 13% (based to TFE model). Our findings reveal that biofuels, solar and hydropower contribute to promote the operational and environmental efficiency of the largest 20 OGC. However, the analysis suggests that while the global energy transition significantly influences and bolsters environmental efficiency, its effect on operational efficiency among these major OGC remains less pronounced and insufficient. [ABSTRACT FROM AUTHOR]

Scheduling workload is a demand response strategy for data centers to reshape electricity usage, which provides an opportunity for them to utilize renewable energy. Enhancing the flexibility of workload scheduling would promote the data center to integrate renewable energy. Considering that the improvement of flexibility in workload scheduling is tightly related to the Quality of Service (QoS) required by IT consumers (ITCs), it becomes desirable for the data center to collaborate with them to further facilitate renewable energy integration in demand response programs. This paper proposes a QoS‐based bi‐level demand response model for the data center, where game theory is adopted to resolve the conflict of interest in the collaboration between the data center and ITCs. At the upper level, the data center is a leader who provides differential monetary incentives to ITCs while dispatching workload to integrate renewable energy. At the lower level, ITCs act as followers who adjust the workload's QoS to enhance the flexibility of workload scheduling. Simulation results show that the proposed model can decrease the operating cost of the data center while increasing the utilization of renewable energy. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [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]

Energy generation and pollutant emissions are two faces of the same coin, as the current energy sources i.e., fossil energy, are still considered to be major sources of greenhouse gases (GHG). Therefore, shifting to cleaner energy sources imposes itself as an inevitable solution to reduce this environmental cost. In this paper, a hybrid system based on the multi-agent approach and Long Short-Term Memory (LSTM) neural networks to forecast the energy production and its carbon dioxide (CO2) emissions and simulate the potential emission reduction in case of switching to renewable energy sources is presented. The proposed system's architecture consists of combining LSTM models with the agent-based technology, where multiple LSTM forecasting models were trained to forecast the production of each type of the studied energies and then estimate the equivalent emitted CO2 and calculate the influence of the renewable energy inputs on the carbon emissions and the fossil fuels consumption. The simulation process consists of two phases: firstly, each forecasting agent uses a specific LSTM model to forecast short-term energy production. Secondly, these agents send the forecasted values to the coordination agent who is responsible for calculating the total CO2 emissions and the benefits of the renewable energy inputs. [ABSTRACT FROM AUTHOR]

As the global transition toward sustainable energy gains momentum, integrating electric vehicles (EVs), energy storage, and renewable energy sources has become a pivotal strategy. This paper analyses the interplay between EVs, energy storage, and renewable energy integration with Indonesia's grid as a test case. A comprehensive energy system modeling approach using PLEXOS is presented, using historical data on electricity generation, hourly demand, and renewable energy, and multiple scenarios of charging patterns and EV adoption. Through a series of scenarios, we evaluate the impact of different charging strategies and EV penetration levels on generation capacity, battery storage requirements, total system cost, renewable energy penetration, and emissions reduction. The findings reveal that optimized charging patterns and higher EV adoption rates, compared to no EVs adoption, led to substantial improvements in renewable energy utilization (+4%), emissions reduction (−12.8%), and overall system cost (−9%). While EVs contribute to reduced emissions compared to conventional vehicles, non-optimized charging behavior may lead to higher total emissions when compared to scenarios without EVs. The research also found the potential of vehicle to grid (V2G) to reduce the need for battery storage compared to zero EV (−84%), to reduce emissions significantly (−23.7%), and boost penetration of renewable energy (+10%). This research offers valuable insights for policymakers, energy planners, and stakeholders seeking to leverage the synergies between EVs and renewable energy integration to pursue a sustainable energy future for Indonesia. [ABSTRACT FROM AUTHOR]

The development of large energy systems based on renewable energy sources is accompanied by an increase in the input capacities of large grid storages. Taking into account the vector for decarbonization and maneuverability, the use of hydrogen as a fuel in the cycle of a diabatic compressed air energy storage (CAES) is a promising scientific and technical direction. This paper analyzes the key performance indicators of a compressed air energy storage in the presence and absence of thermal energy recovery within the cycle. In addition, an assessment was made of the prospects for the use of a methane-hydrogen mixture in gas turbines. At the end of the paper, a calculation of the process of plasma pyrolysis of methane is given as one of the possible methods for the production of hydrogen for use in energy purposes. [ABSTRACT FROM AUTHOR]

Due to the non-deterministic and probabilistic qualities of renewable energy resources (RER), integrating these resources has posed a challenge for energy companies and government policy planners. Hybrid power systems require frequent voltage regulation to address the changes in renewable generation and facilitate voltage management. This leads to an increment in the operating time of the tap changer in the power transformer, thus resulting in accelerated degradation of the on-load tap changer (OLTC) device. The primary focus of this paper is to optimally manage the penetration level of renewable generation while maintaining the minimum time for proper operation of voltage regulation devices. Accordingly, the major contribution of this paper is to address the switching cycle issues of the on-load tap-changing transformer. Initially, a framework is proposed to optimize the location and size of renewable power generation using a multi-objective cuckoo search optimization algorithm. The main goal here is to reduce power losses and tap changer operations while improving the system voltage profile under different levels of renewable energy penetration. The optimization problem takes into consideration the fluctuating nature of wind speed and solar irradiance for sunny and cloudy days over 24 h. The framework has been applied to the IEEE 57-bus and 118-bus systems with different load levels. The performance of the proposed approach has been benchmarked by comparing it with the genetic optimization algorithm to identify the higher potential buses for renewable generation allocation. The cuckoo search algorithm (CSA) shows outstanding results in reducing the number of switching cycles to about (37 – 43) % whereas the genetic algorithm (GA) only (17 – 18). In this sense, the number of changes in tap position when using the CSA is 1956 for sunny days and 1763 for cloudy days compared to GA 2558 for sunny days and 2547 for cloudy days. The voltage profiles for both algorithms are maintained in the range of (1.06 and 0.94) per unit. The results affirm the effectiveness of the proposed approach in determining the optimal placement and size of RER with voltage profile improvement and reduction in the switching cycles of OLTC. [ABSTRACT FROM AUTHOR]

To achieve a more ecologically friendly energy transition by the year 2050 under the European "green" accord, hydrogen has recently gained significant scientific interest due to its efficiency as an energy carrier. This paper focuses on large-scale hydrogen production systems based on marine renewable-energy-based wind turbines and tidal turbines. The paper reviews the different technologies of hydrogen production using water electrolyzers, energy storage unit base hydrogen vectors, and fuel cells (FC). The focus is on large-scale hydrogen production systems using marine renewable energies. This study compares electrolyzers, energy storage units, and FC technologies, with the main factors considered being cost, sustainability, and efficiency. Furthermore, a review of aging models of electrolyzers and FCs based on electrical circuit models is drawn from the literature and presented, including characterization methods of the model components and the parameters extraction methods, using a dynamic current profile. In addition, industrial projects for producing hydrogen from renewable energies that have already been completed or are now in progress are examined. The paper is concluded through a summary of recent hydrogen production and energy storage advances, as well as some applications. Perspectives on enhancing the sustainability and efficiency of hydrogen production systems are also proposed and discussed. This paper provides a review of behavioral aging models of electrolyzers and FCs when integrated into hydrogen production systems, as this is crucial for their successful deployment in an ever-changing energy context. We also review the EU's potential for renewable energy analysis. In summary, this study provides valuable information for research and industry stakeholders aiming to promote a sustainable and environmentally friendly energy transition. [ABSTRACT FROM AUTHOR]

• A life cycle assessment (LCA) of solid recovered fuel (SRF) was conducted. • SRF production process contributes to about 35.6 kg CO 2 -eq per ton. • A maximum of −1752.03 kg CO 2 -eq was obtained with about 80 % of SRF biogenic carbon. • A footprint of −542.09 to −1729.05 kg CO 2 -eq can be found due to coke substitution. • The study recommended SRF production to mitigate the global carbon footprint. Solid recovered fuel (SRF) from non-recyclable waste obtained from source separation and mechanical treatments can replace carbon coke in cement plants, contributing to the carbon neutrality. A life cycle assessment (LCA) of the SRF production from non-recyclable and selected waste was conducted in an Italian mechanical treatment plant to estimate the potential environmental impacts per ton of SRF produced. The analysis would contribute to evaluate the benefits that can be obtained due to coke substitution in best- and worst-case scenarios. The avoided impacts achieved were assessed, together with an evaluation of the variables that can affect the environmental benefits: SRF biogenic carbon content (in percentage of paper and cardboard); transportation distances travelled from the treatment plant to the cement kiln; the renewable energy used in the mechanical facility. On average, about 35.6 kgCO 2 -eq are generated by the SRF transportation and production phase. These impacts are greatly compensated by coke substitution, obtaining a net value of about −1.1 tCO 2 -eq avoided per ton of SRF. On balance, the global warming potential due to SRF production and consumption ranges from about −542 kgCO 2 -eq to about −1729 kgCO 2 -eq. The research recommended the use of SRF to substitute coke in cement kilns also in low densely-populated areas to mitigate environmental impacts and achieve carbon neutrality at a global level. [ABSTRACT FROM AUTHOR]

With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

Advancements in new technologies, a reduction in CO2 emissions, and the rising demand for energy are causing a growth in the share of renewable energy sources. In distribution networks, an increasing number of distributed generators (DGs) makes the utility grid's protection complex and demanding. Vector surge and rate-of-change-of-frequency are the established anti-islanding protection methods, recognizing that the standard paradigm for protection, involving distributed generation, cannot be set only once but has to be continuously updated following the requirements and changes in the system. One of the requirements is active participation in the preservation of system frequency and voltage, which can be interrupted if the DG trips and disconnects from the utility grid. Anti-islanding protection and spurious tripping can be avoided by implementing new algorithms and techniques. This paper presents a novel protection scheme based on a voltage frequency differential. The proposed algorithm employs remote and local frequency measurements in such a manner that, for the occurrence of a frequency difference, it is assumed that the DG is in an islanding state. In this article, we demonstrate the feasibility of the algorithm through numerical analysis of grid events and laboratory testing emulating real grid-measured values. The test results show that the algorithm is resilient to false tripping for non-islanding events and more reliable than conventional methods in islanding detection. The algorithm can be set to low-frequency differential values, drastically reducing the non-detection zone in any DG type, regardless of its size and voltage level at the point of common coupling. Unlike standard anti-islanding methods, the algorithm supports the ability of the DG to fault-ride through demand. [ABSTRACT FROM AUTHOR]

Renewable energy systems are mostly used in the world due to their inexhaustible and nonpolluting production. As a result of a large utilization of these energy sources in different areas, the electricity production rate is increasing every day. Previous studies clarified uses, modeling, configuration, energy management operation, and optimization objectives based on different energy sources. For this reason, this paper focuses on an overview of multi energy systems as renewable and conventional power sources with the integration of an energy storage system coupled to the on-off electrical network. Furthermore, a survey is done regarding global energy production, configuration energy systems, energy storage systems, power management strategies, and optimization methods based on different hybrid energy systems. Multiple optimization approaches have been implemented to reach the global best solution for the hybrid power systems. To ensure the best optimization result, it is preferable to take hybrid optimization methods into consideration. These methods have been invented recently and have proved their efficacy and performance mainly in power systems. [ABSTRACT FROM AUTHOR]

This paper analyzes the impact of renewable energy consumption, total factor productivity (TFP), income, imports, and exports on consumption-based CO2 emissions in Turkey from 1990 to 2019, utilizing the Autoregressive Distributed Lagged (ARDL) method. The findings indicated that the use of renewable energy, total factor productivity and exports negatively influence CO2 emissions. On the other hand, the positive impact of income and imports on CO2 emissions was found. The negative impact of renewable energy consumption and total factor productivity highlights the importance of implementing environmentally friendly measures in the energy sector (particularly raising the proportion of renewable energy in overall energy consumption) and technological innovation. [ABSTRACT FROM AUTHOR]

With the continuous increase in global energy demand and growing environmental awareness, the utilization of renewable energy has become a worldwide consensus. In order to address the challenges posed by the intermittent and unpredictable nature of renewable energy in distributed power distribution networks, as well as to improve the economic and operational stability of distribution systems, this paper proposes the establishment of an active distribution network capable of accommodating renewable energy. The objective is to enhance the efficiency of new energy utilization. This study investigates optimal scheduling models for energy storage technologies and economic-operation dispatching techniques in distributed power distribution networks. Additionally, it develops a comprehensive demand response model, with real-time pricing and incentive policies aiming to minimize load peak–valley differentials. The control mechanism incorporates time-of-use pricing and integrates a chaos particle swarm algorithm for a holistic approach to solution finding. By coordinating and optimizing the control of distributed power sources, energy storage systems, and flexible loads, the active distribution network achieves minimal operational costs while meeting demand-side power requirements, striving to smooth out load curves as much as possible. Case studies demonstrate significant enhancements during off-peak periods, with an approximately 60% increase in the load power overall elevation of load factors during regular periods, as well as a reduction in grid loads during evening peak hours, with a maximum decrease of nearly 65 kW. This approach mitigates grid operational pressures and user expense, effectively enhancing the stability and economic efficiency in distribution network operations. [ABSTRACT FROM AUTHOR]

Demand-side flexible load resources, such as Electric Vehicles (EVs) and Air Conditioners (ACs), offer significant potential for enhancing flexibility in the power system, thereby promoting the full integration of renewable energy. To this end, this paper proposes an optimal allocation method for demand-side flexible resources to enhance renewable energy consumption. Firstly, the adjustable flexibility of these resources is modeled based on the generalized energy storage model. Secondly, we generate random scenarios for wind, solar, and load, considering variable correlations based on non-parametric probability predictions of random variables combined with Copula function sampling. Next, we establish the optimal allocation model for demand-side flexible resources, considering the simulated operation of these random scenarios. Finally, we optimize the demand-side resource transformation plan year by year based on the growth trend forecast results of renewable energy installed capacity in Jiangsu Province from 2025 to 2031. [ABSTRACT FROM AUTHOR]

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverter-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative in enhancing the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state-space model and eigenvalues analysis are presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained, considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small-signal stability of the entire system. And the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. A case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations. [ABSTRACT FROM AUTHOR]

This paper deals with the problems related to power stability issues in the isolated wind-solar based renewable energy system. The stability issues in such system are produced mainly due to unbalanced loading, distortion of load current and intermittent nature of renewable energy sources. To overcome these problems, A voltage source converter (VSC) is used in proposed literature. The VSC is driven using a time domain-based signal decomposition algorithm consisting a 3-phase dual reduced order generalized integrators frequency Locked loop (DROGI-FLL). The 3 phase DROGI FLL has the inherent abilities of noise rejection and error tracking, which improves the system stability and maintains the voltage and frequency of the system constant under transient conditions. The transient conditions are simulated by varying the loading condition, solar irradiance and wind speed in the system. Apart from stability issues this system also deals with the issues related to reactive composition, natural current compensation and operation of SPV system at maximum power point (MPP). A perturb and observe (P&O) maximum power point tracking (MPPT) is employed for the working of solar photovoltaic systems (SPV) system at MPP and to maximize the utilization of renewable energy. The neutral current compensation is achieved by using a star-double delta transformer. This entire system is developed and tested in the MATLAB/SIMULINK environment.. [ABSTRACT FROM AUTHOR]