Renewable Energy最新文献

{"title":"Challenges and future directions to improve the hydrogen economy","authors":"Kathirvel Brindhadevi ,&nbsp;S.K. Kamarudin ,&nbsp;Arivalagan Pugazhendhi","doi":"10.1016/j.renene.2025.124560","DOIUrl":"10.1016/j.renene.2025.124560","url":null,"abstract":"<div><div>Hydrogen has significant potential as a versatile energy carrier in global energy conversion. Renewable and non-renewable sources of hydrogen can be utilized to produce environmentally friendly hydrogen. Biogasification, steam methane reforming, electrolysis, and petrochemical water splitting are the most common production methods. The demand for hydrogen remains primarily driven by oil refinement, which produces more than 99 % of the fuel including automative fuel cell applications. For hydrogen to be a proper climate solution, it must be based on fossil fuel infrastructure. Despite these challenges, industry, transportation, and power generation present promising opportunities for the hydrogen economy. The process of hydrogen production, storage, distribution, and utilization for fuel involves several steps. A comprehensive analysis of the current state of hydrogen is presented here, along with a discussion of its future trajectory, including advances in production technology, fuel application, infrastructure development, and applications in several industries. It will take substantial investments and collaborations to transition from laboratory-scale to large-scale commercial hydrogen production. It is crucial to have critical discussions on cost, infrastructure gaps, and technological limitations if hydrogen is to realize its full potential in decarbonizing global energy systems.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124560"},"PeriodicalIF":9.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal power allocation and capacity configuration based on variable cut-off frequency low-pass filtering for photovoltaic with hybrid energy storage system","authors":"Xiaobo Kan ,&nbsp;Xun Ma ,&nbsp;Jingying Yao ,&nbsp;Bifeng Xiong ,&nbsp;Yu Zhao","doi":"10.1016/j.renene.2025.124526","DOIUrl":"10.1016/j.renene.2025.124526","url":null,"abstract":"<div><div>Photovoltaic (PV) power generation is affected by intermittent solar radiation, leading to fluctuations in output power and reducing the stability and reliability of PV systems. In general, a hybrid energy storage system (HESS) combined with a PV system is employed to smooth PV power fluctuation. However, the traditional algorithms for balancing the capacity of HESS, power fluctuations, and life cycle costs (LCC) remain challenging. To address this challenge, a modified method of variable cut-off frequency low-pass filtering (VFLPF) is developed to determine the capacity of battery and supercapacitor (SC) in HESS, as well as balance the relationship between PV power fluctuations and total energy system capacity (TESC). Additionally, <em>Z</em>_E and <em>Z</em>_p are adopted as metrics for evaluating the total energy system capacity and reference power, respectively, specifically employed to mitigate the maximum fluctuation rate (MFR) in PV systems. Moreover, the presented algorithm is validated by the photovoltaic module combined with the hybrid energy storage system (PVM-HESS) and the photovoltaic array combined with the hybrid energy storage system (PVA-HESS). In the presented PVM-HESS and PVA-HESS, the metrics <em>Z</em>_E are respectively reduced by 2.65–2.94 % and 20–54.10 % compared to the traditional fixed cut-off frequency low-pass filtering (FFLPF) strategies of S.Ⅰ (cut-off frequency of 160 Hz) and S.Ⅱ (cut-off frequency of 750 Hz), while the <em>Z</em>p is reduced by 3.3–45.62 % and 3.31–78 %, respectively. The life cycle costs determined by the presented algorithm are reduced by 7.71 % and 11.10–21.52 %. Furthermore, a three-port DC-DC converter of 450 W is designed to connect the DC Bus with the PV module and the hybrid energy storage system, in which the MFR of PV output power is reduced by 23.77 %. Finally, a 20 kWp PVA combined with the hybrid energy storage system optimises power allocation and capacity configuration while reducing the MFRs throughout the year by 0.07–64.53 %. In conclusion, the presented algorithm and strategy are an effective technical solution for reducing total energy capacity and reference power when smoothing power fluctuations, as well as providing theoretical support for coordinated operation of storage energy equipment in a hybrid energy storage system.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124526"},"PeriodicalIF":9.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact-driven environmental and performance evaluation of microalgae biodiesel blends for sustainable micro gas turbine operation: An experimental and life cycle approach","authors":"Hanzheng Sun ,&nbsp;A. Anderson","doi":"10.1016/j.renene.2025.124559","DOIUrl":"10.1016/j.renene.2025.124559","url":null,"abstract":"<div><div>The current study aims to develop a concept of using the blended gaseous fuel along with the biofuel blends to reduce the emission of the harmful pollutants without affecting the engine performance. The microalgae biofuel derived from <em>Chlorella vulgaris</em> was examined at the concentration of 10 %vol and 30 %vol with neat Jet-A. The microalgae undergone microwave assisted pyrolysis process to the production biofuel. The produced biofuel dispersed with the Jet-A fuel at the concentration of 10 %vol and 30 %vol to form B10 and B30. In addition to above biofuel blends, the biogas was injected at the concentration of 10 L per minute. The experimental data were analyzed on thrust output, thrust specific fuel consumption, turbine inlet temperature, and emissions of oxides of nitrogen, carbon monoxide, and carbon dioxide. Use of the biofuel reduces the production of thrust compared to the Jet-A fuel. This was mainly due to the lower heating value and poor calorific value of the biofuel derived from the microalgae. The results revealed that the use of microalgae biodiesel along with biogas blends improves specific fuel consumption which also reduce emissions of pollutants such as, NOx, CO and CO₂ without any negative effects on the thrust output compared to Jet-A fuel. The fuel blend with 10 % biofuel with biogas exhibited the highest thrust output and lowest specific fuel consumption across various six engine speeds. Meanwhile the B30 blend with biogas blends showed significant reduction in NOx, CO, and CO₂ emissions but there is a potential reduction in the thrust. An additional life cycle assessment further validated the environmental sustainability of the proposed fuel blends by highlighting their potential to reduce greenhouse gas emissions and fossil energy use.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124559"},"PeriodicalIF":9.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive ensemble of surrogates for efficient fatigue reliability analysis of offshore wind turbines","authors":"Jinsheng Wang ,&nbsp;Chao Chen ,&nbsp;Philippe Duffour ,&nbsp;Paul Fromme","doi":"10.1016/j.renene.2025.124553","DOIUrl":"10.1016/j.renene.2025.124553","url":null,"abstract":"<div><div>Offshore wind turbines (OWTs) are crucial to the global transition towards renewable energy, but they operate under harsh marine conditions where fatigue damage from wind- and wave-induced loads is a critical design concern. Assessing fatigue reliability is further complicated by uncertainties in environmental and structural parameters, and conventional approaches such as Monte Carlo simulation (MCS) remain prohibitively expensive. To address this challenge, this study develops an adaptive ensemble of surrogates (AEOS) that integrates Kriging, Bayesian support vector regression, and polynomial chaos Kriging. A novel weighting strategy that balances local and global error measures, together with a reward-based learning function allocation scheme and a hybrid stopping criterion, enables efficient and accurate active learning. The proposed AEOS is validated on benchmark problems and a monopile-supported OWT case study, achieving failure probability estimates with less than 1.5% relative error while reducing computational cost by more than 95% compared to MCS. Sensitivity analysis further reveals that wind conditions and fatigue strength parameters dominate fatigue reliability outcomes. AEOS provides an efficient, accurate, and flexible framework for fatigue reliability assessment, supporting risk-informed maintenance, life extension, and sustainable operation of offshore wind infrastructure.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124553"},"PeriodicalIF":9.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the green revolution: Exploring the impact of outward FDI, green transition, governance quality, and industrial structure on renewable energy penetration","authors":"Mohammad Haseeb ,&nbsp;Mohd Shuaib ,&nbsp;Md Emran Hossain ,&nbsp;Fei Fan","doi":"10.1016/j.renene.2025.124554","DOIUrl":"10.1016/j.renene.2025.124554","url":null,"abstract":"<div><div>The escalating global demand for sustainable energy solutions underscores the urgent need to understand the drivers of renewable energy adoption, aligning closely with Sustainable Development Goal 7 (SDG 7). Hence, this study explores how outward foreign direct investment (FDI), green transition strategies, industrial activity, urbanization, and governance quality shape green energy penetration across five developed European economies between 2000 and 2022. Employing the CS-ARDL method, the results indicate that outward FDI, effective governance, and green transition initiatives enhance the renewable energy penetration. At the same time, rapid industrial growth and urban expansion tend to hinder it. Causality tests reveal that outward FDI, industrial growth, and urbanization have a one-way effect on renewable energy use. In contrast, governance quality and green transitions share a two-way relationship with renewable energy penetration. The findings highlight the critical role of institutional strength and international investment in promoting renewable energy. Policymakers are encouraged to prioritize strong governance frameworks and environmentally aligned FDI strategies, while integrating sustainability into urban and industrial planning to support a broader green energy shift.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124554"},"PeriodicalIF":9.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green capacity investment with declining cost due to technological innovations under subsidy withdrawal risk","authors":"Yanyun Liu,&nbsp;Ruili Zhao,&nbsp;Yanqing Wang,&nbsp;Baiqing Sun","doi":"10.1016/j.renene.2025.124433","DOIUrl":"10.1016/j.renene.2025.124433","url":null,"abstract":"<div><div>In recent years, driven by technological innovations, the investment costs of renewable energy projects are continuously decreasing. Subsidies initially implemented to stimulate investment tend to be withdrawn gradually. This study analyzes the impact of the lump-sum investment subsidy with withdrawal risk on investment and social welfare in a dynamic framework with uncertain demand and technological innovations. Assuming that the arrivals of technological innovations follow a Poisson process and each innovation reduces investment cost by a fixed factor, We find that increasing the subsidy size or withdrawal risk accelerates investment while reduces capacity. An opposite effect is found when the arrival rate of technological innovations is increased or cost reduction factor is decreased. When the withdrawal risk is significantly low or nonexist, a larger arrival rate of technological innovations or smaller cost reduction factor increases the optimal subsidy level required to maximize welfare. When aiming to achieve a capacity target lower than the optimal capacity level without a subsidy, the lower the target setting, the higher the required optimal subsidy level, which is more significant for a higher arrival rate or a lower cost reduction factor.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124433"},"PeriodicalIF":9.1,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A study on long-term operation and performance loss rates of various PV technologies in eastern Poland","authors":"Slawomir Gulkowski ,&nbsp;José Vicente Muñoz Díez ,&nbsp;Jorge Aguilera Tejero ,&nbsp;Piotr Dragan ,&nbsp;Gustavo Nofuentes","doi":"10.1016/j.renene.2025.124548","DOIUrl":"10.1016/j.renene.2025.124548","url":null,"abstract":"<div><div>Despite Poland's rapid PV deployment, long-term system performance studies are virtually nonexistent. This paper analyzes the four-year performance of four small PV systems in Bordziłówka, eastern Poland, each using a different technology: polycrystalline silicon (pc-Si), amorphous silicon (a-Si), cadmium telluride (CdTe), and copper indium gallium selenide (CIGS). The analysis focuses on energy yields, yield losses, performance metrics and performance loss rates (<em>PLR</em>, in %·y⁻¹), the latter calculated via Classical Series Decomposition and Year-on-Year methods. Pc-Si outperformed the others, with an average annual yield 2 % higher than CIGS and 25–60 % higher than a-Si and CdTe. Performance ratio (PR) values ranged from 0.88 to 0.85 for pc-Si and 0.87–0.82 for CIGS, while a-Si and CdTe showed lower PR (0.66–0.63 and 0.46–0.26, respectively). CdTe exhibited the highest degradation with <em>PLR</em> of −15.2 ± 4.45 %·y⁻¹ (YoY), contrasting with pc-Si's <em>PLR</em> −0.67 ± 0.89 %·y⁻¹ (YoY), which aligns with warranty standards and global literature.</div><div>Although based on a limited sample, the results offer valuable insights for PV deployment not only for Poland, but for cold-temperate climates, with relevance to Eastern Europe, Central Asia, and northern North America. The study highlights the importance of long-term, region-specific monitoring to guide technology selection and energy policy.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124548"},"PeriodicalIF":9.1,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modified deep reinforcement learning for frequency regulation in active distribution systems with soft open points, storage units and electric vehicles","authors":"Ahmed M. Taher ,&nbsp;Shady H.E. Abdel Aleem ,&nbsp;Saad F. Al-Gahtani ,&nbsp;Ziad M. Ali ,&nbsp;Hany M. Hasanien","doi":"10.1016/j.renene.2025.124537","DOIUrl":"10.1016/j.renene.2025.124537","url":null,"abstract":"<div><div>As an effective approach to achieving the smart grid concept and reducing carbon emissions, the integration of renewable energy sources and storage devices is increasing. However, with the growing demand for high-power charging, the electrical grid faces significant challenges as electric vehicle (EV) adoption rises, particularly in the presence of stochastic energy sources. Consequently, the need for robust regulation strategies to manage distribution system uncertainties, especially in frequency regulation, is becoming more critical. Distribution systems, interconnected through multi-terminal soft open points (SOPs), are evolving into highly controllable, integrated, and flexible architectures. Performance is further enhanced by incorporating a dedicated terminal for hybrid hydrogen energy storage. Additionally, the integration of vehicle-to-grid (V2G) and grid-to-vehicle (G2V) operations has been explored. To effectively manage these operational frameworks, a modified deep reinforcement learning (RL) strategy based on the deep deterministic policy gradient (DDPG) algorithm is proposed. Multi-agent deep RL is employed, generating multiple control signals per agent based on reward functions derived from a quadratic optimization function within the model predictive control (MPC) framework. To ensure an optimal control action waveform and enhance system performance, each DDPG deep RL agent's control action value is scaled by its observation value, integral, and derivative, integrated through a filter element. When applying the proposed modified deep RL strategy alongside the components, the rate of frequency change and power transfer fluctuations achieved minimal steady-state errors in the range of × 10⁻⁸, with significantly damped overshoot and undershoot levels. This approach effectively maintains system performance, outperforming other simulated scenarios.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124537"},"PeriodicalIF":9.1,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the impact of non-similar collectors in advanced solar network design","authors":"Hassan Hajabdollahi ,&nbsp;Farzaneh Hajabdollahi ,&nbsp;Amin Saleh","doi":"10.1016/j.renene.2025.124486","DOIUrl":"10.1016/j.renene.2025.124486","url":null,"abstract":"<div><div>In this paper, a solar network considering flat plate collector (FPC) is optimized considering both efficiency and annual cost as objective functions. Two distinct scenarios are explored: a similar case and a non-similar case, allowing for the selection of collectors with different parameters. The study investigates three cases involving 2–4 collectors in the network, leading to the consideration of 6 design parameters including mass flow rate, number and diameter of tubes, collector length and width, as well as insulator thickness, in the similar case and 12–24 design parameters in the non-similar case. The optimization results revealed that, for all studied examples, the results from the similar case were consistently outperformed by those from the non-similar case. The maximum efficiency improved by 1.63 %–1.94 % in the non-similar case as compared with the similar case. The annual cost is improved by 1.24 %–2.62 % in the final optimum solution. For example, the maximum efficiency increases from 0.7068 in the similar FPC case to 0.7183 in the non-similar configuration for two collectors. The mentioned values were respectively 0.7195 and 0.7333 in the four collectors. These improvements offer real-world benefits, including higher energy yield and lower operating costs—key to accelerating solar adoption.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124486"},"PeriodicalIF":9.1,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145216602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization strategy for green wind energy storage systems based on natural resources and enterprise load","authors":"Jingwen Dong,&nbsp;Yibai Wang,&nbsp;Yang Jing,&nbsp;Jiaming Shi,&nbsp;Mengfan Chen,&nbsp;Zhi Liu,&nbsp;Na Sun,&nbsp;Hui Huang,&nbsp;Jie Ji","doi":"10.1016/j.renene.2025.124545","DOIUrl":"10.1016/j.renene.2025.124545","url":null,"abstract":"<div><div>This study employs a hybrid NRBO-ICEEMDAN algorithm (combining Newton-Raphson Based Optimization and Improved Complete Ensemble Empirical Mode Decomposition) to optimize wind-storage strategies for enterprise energy systems, achieving significant cost reductions and profit growth. The results show that under the optimization model of maximum load matching rate, cost, and benefit, the cost of wind energy equipment accounts for 61.31 % of the total cost and the electricity sales revenue is 74.6434 million yuan under the operation of a single wind energy equipment. The proportion of peak shaving, valley filling, and carbon reduction benefits is not high; Under the operation of a single energy storage system, the cost of energy storage equipment accounts for 39.27 % of the total cost, with a revenue of 12.5991 million yuan, highly concentrated on the peak shaving and valley filling functions of the energy storage system. Considering the overall operation, the total cost accounts for 83.7 % and the revenue is as high as 114655500 yuan, which improves the comprehensive efficiency of the energy system. At the same time, with the increase of operation time, the expansion and maintenance investment of wind energy equipment and energy storage equipment, the comprehensive operation strategy benefits are more considerable. Research has shown that the optimization strategy of green energy wind energy storage plays a decisive role in reducing total costs and increasing benefits. This study provides a new methodology and decision support for optimizing green energy wind energy storage strategies for natural resources and enterprise loads, emphasizing the importance of comprehensive consideration of economic and environmental goals.</div></div>","PeriodicalId":419,"journal":{"name":"Renewable Energy","volume":"256 ","pages":"Article 124545"},"PeriodicalIF":9.1,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}