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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]

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]

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]

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]

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]

The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies. • Applied SDG policies focused on energy technology RD&D are presented. • The stochastic characteristics of energy technology investments are examined. • Carbon-reducing policies are recommended for the top five economies. • Energy technologies are perused through artificial intelligence approach. [ABSTRACT FROM AUTHOR]

In the background of exhaustion of the traditional fossil energy sources and environmental deterioration, developing renewable energy has become a strategic choice for countries to achieve energy sustainable utilization and carbon neutrality target. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. However, the commonly used weight calculation methods in the existing renewable energy evaluation have obvious shortcomings, such as the randomness of the subjective method is strong and the gap in the weight allocation of the objective method is too large, which affect the reliability and accuracy of the sorting result. In this paper, a novel weight calculation method based on non-dominated sorting genetic algorithm (NSGA-II) is proposed, and is applied to renewable energy evaluation. The study in this paper focuses on methodology. Firstly, for the linear normalized and Zeros normalized evaluation data, the differences between renewable energy plans in the two normalized evaluation data are measured, and the ranking deviations of the two normalized data are calculated. Then, the multi-objective weight solving model is constructed in terms of plans differences minimization and ranking vectors deviations minimization. The NSGA-II algorithm is applied to the optimization of multi-objective functions to find the Pareto non-dominated solution, so as to determine the weight values of each evaluation index. Finally, the TOPSIS method is used to determine the relative closeness value of each plan, and the rankings of renewable energy technical plans are achieved. Based on the actual renewable energy development data of a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some popular renewable energy evaluation methods. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Apply non-dominated sorting genetic algorithm II to determine the index weights. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

This study aims to investigate the factors of renewable energy consumption in the fifth Technology Revolution with specific evidence from ASEAN countries. The study applies an autoregressive distributed lag (ARDL) approach. The paper also uses the unrestricted fixed and random panel data methods. The manuscript identifies significant factors such as technological innovation, governmental policies, public awareness, electricity consumption, country population, foreign direct investment inflows, imports, exports, and economic growth that have influenced the renewable energy sector in these nations. This study also investigates the determinants that influence renewable energy in the context of international integration and the fifth technology revolution in ASEAN countries. The research analyzes data spanning two decades, from 2000 to 2022, through a combination of econometric modeling and machine learning techniques. Preliminary findings indicate that technological innovation, government policies, and public awareness significantly affect renewable energy consumption in these countries. The empirical results offer insights for policymakers and stakeholders in leveraging technological advancements for sustainable energy development. The findings from this study on the determinants of renewable consumption in the context of the Fifth Technology Revolution in ASEAN countries also have several important policy implications for the sustainable development goal. • This study aims to investigate the factors of renewable energy consumption in the fifth Technology Revolution. • The study uses panel data analysis, and the paper identifies significant factors that have influenced the renewable energy sector. [ABSTRACT FROM AUTHOR]

Modular Gravity Energy Storage (M-GES) systems are emerging as a pivotal solution for large-scale renewable energy storage, essential for advancing green energy initiatives. This study introduces innovative capacity configuration strategies for M-GES plants, namely Equal Capacity Configuration (EC) and Double-Rate Capacity Configuration (DR), tailored to optimize energy storage efficiency and stability. Through comprehensive MATLAB/Simulink simulations, we demonstrate each configuration's distinct power characteristics and operational advantages. Our findings reveal that while the EC configuration offers enhanced power accuracy and stability, it requires a larger number of units. In contrast, the DR configuration, characterized by fewer but larger units, shows a trade-off with reduced power stability. This paper contributes significantly to the field by presenting a first-of-its-kind comparative analysis of these configurations, offering insights into their practical applications and scalability. The proposed strategies and findings lay a foundation for future research and development in gravity energy storage systems, marking a step forward in pursuing sustainable and reliable energy solutions. [Display omitted] • Two typical unit capacity configuration strategies for M-GES power plants are proposed. • The unit scheduling method of the M-GES power plant is proposed. • The coordination control method is provided for each proposed configuration strategy. • Equal capacity configuration has better power accuracy but requires more units. • Double rate configuration needs fewer but larger units and less power stability. [ABSTRACT FROM AUTHOR]

In this era of global warming the importance of climate risk cannot be understated, and finding ways to reduce climate risk is a topic worthy of study. In this paper, we innovatively examine the role of renewable energy technology innovation on climate risk in China. In addition to their linear relationship, we also investigate the asymmetric and heterogeneous impact, detect the impact channels, and find that (1) increased renewable energy technology innovation can effectively alleviate the climate risk situation. Accordingly, the development of renewable energy technology innovation can make a significant contribution to CR abatement. (2) Pronounced impacts of renewable energy technology innovation on climate risk can be observed in the higher quantiles (75th and 90th) of climate risk. (3) Renewable energy technology innovation is a powerful weapon for eradicating climate risk in provinces with a higher level of government fiscal expenditure. And (4) renewable energy technology innovation has an impact on climate risk by facilitating energy consumption efficiency, which is a necessary mediator. These conclusions inspire us to put forward several corresponding policy implications for better climate risk governance and renewable energy technology innovation development. [ABSTRACT FROM AUTHOR]

To achieve the goal of "carbon peaking and carbon neutrality", China is vigorously developing renewable energy. This paper aims to examine the major contributors to regional inequality in renewable energy consumption by analyzing the 30 provinces in China. We have analyzed the inequality of China's renewable energy consumption with Dagum Gini coefficient, and then use the Generalized Divisia Index Model (GDIM) to decompose the influencing factors contributing to the inequality of renewable energy consumption. The main conclusions are summarized as follows: First, renewable energy consumption was higher in the western region than in the central and eastern regions, and the regional inequality in renewable energy consumption have increased over time. Second, the study reveals that inter-group disparity is the primary source of regional inequality in renewable energy consumption in China. Third, at the national level, the results of the GDIM decomposition show that economic development continues to rely on fossil energy consumption, which negatively impacts the low-carbon transition of energy. Given China's complex geographical conditions, it is crucial for different provinces to develop their own strategies for renewable energy development, taking into account unique resources and challenges. [ABSTRACT FROM AUTHOR]

Identifying the research topics of China's energy transition policy and predicting future research trends are crucial for policymakers to make informed decisions and advance the energy transition. This study applied the Latent Dirichlet Allocation (LDA) to extract 26 major research topics from the 13,976 abstracts of Chinese policy research papers in web of science (WOS), conceptualized the five most popular topics and used the ARIMA model to predict trends over the next 36 months. The results show that except for Economic and Environmental Impact of Renewable Energy Consumption (Topic13), which will first experience unanticipated fluctuations and then show strong growth capacity, all other topics will continue to remain positive growth trend. Research and Development (Topic3) is driven by the urgency of China's energy transformation. Economic and Environmental Impact of Renewable Energy Consumption (Topic13) is driven by the potential for the development of renewable energy. Economic Impact of Climate Change (Topic26) is driven by the climate change debate. Economic Growth, Urbanization, and Energy Consumption (Topic7) is driven by a discussion of their relationship and the mechanisms influencing them. Regional Efficiency and Productivity Analysis (Topic19) is driven by regional differences in China's energy policies. [ABSTRACT FROM AUTHOR]

This research investigates the relationship between greenhouse gas (GHG) emissions and energy production and consumption patterns in 122 countries over the period from 1990 to 2020. Particular attention is paid to the role of different types of energy, including renewable, hydro and nuclear energy, as well as oil, gas and coal, in shaping GHG emissions. Unlike previous studies, the paper analyzes the full range of energy resources and focuses on different quantiles of data using the quantile-quantile regression (QQR) method. The results of this approach are compared with traditional quantile regression (QR) to assess its validity. Among the findings of this study are: (1) different parts of the energy mix have a heterogeneous impact on GHG emissions in different quantiles; (2) energy consumption patterns play a more significant role in shaping GHG emissions than production patterns; (3) increasing production and consumption of fossil fuels does not necessarily increase GHG emissions; (4) similarly, the development of renewable energy sources is not always accompanied by a reduction in GHG emissions. Our general conclusion is that existing climate policy requires significant diversification to not be focused only on renewable energy, which impact on GHG emissions is not as homogeneous as it usually considered, and which cannot solve the problem of raising emissions solely. Instead of this, it could be more rational to focus on the searching the ways of hydrocarbon industries sustainable development and support them in this journey, especially in the field of Scope 2 and Scope 3 operations management. • Impact of energy consumption and production on GHG emissions were analyzed for 122 countries in 1990–2020. • Quantile and Quantile-on-Quantile regression were used to catch the specifics of energy consumption and production patterns. • Two temporal breakpoints (1999/2000 and 2009/2010) were introduced to catch shifts in variables dependencies. • The influence of fossil fuels on GHG emissions is not homogeneous as it usually considered, the same is fare for renewables. • A promising option to reduce GHG emissions is carbon capture, utilization and storage (CCUS). [ABSTRACT FROM AUTHOR]