Energy Reports最新文献

{"title":"Enhancing PEM fuel cell efficiency through bio-inspired MPPT under variable operating conditions","authors":"Fatima Zohra Kebbab ,&nbsp;Mohit Bajaj ,&nbsp;Vojtech Blazek ,&nbsp;Lukas Prokop","doi":"10.1016/j.egyr.2025.108999","DOIUrl":"10.1016/j.egyr.2025.108999","url":null,"abstract":"<div><div>The aim of this paper is to develop and evaluate a nature-inspired metaheuristic strategy for Maximum Power Point Tracking (MPPT) strategy in Proton Exchange Membrane Fuel Cells (PEMFCs), whose efficiency is highly sensitive to dynamic operating conditions such as cell temperature and the partial pressures of hydrogen and oxygen. These fluctuations continually shift the system’s Maximum Power Point (MPP), necessitating adaptive control methods to maintain optimal power extraction. This study introduces a novel MPPT technique based on the Horse Herd Optimization Algorithm (HOA), a recent bio-inspired metaheuristic modeled on the social behavior of horse populations. To the best of our knowledge, this work presents the first application of HOA to PEMFC systems. A comprehensive dynamic model is constructed, integrating the electrochemical characteristics of a 50 kW PEMFC stack, a DC-DC boost converter, and an adaptive MPPT controller guided by HOA. The algorithm adjusts the converter’s duty cycle by mimicking behavioral mechanisms—such as grazing, hierarchy, sociability, imitation, defense, and roaming—organized across age-based groups to enhance convergence speed and accuracy. The effectiveness of the HOA-based MPPT is benchmarked against the Cuckoo Search Optimization (CSO) method under various conditions, including standard operation, temperature variations (328 K to 348 K), and pressure fluctuations (1.0–2.0 atm). Simulation results using MATLAB/Simulink demonstrate that the HOA algorithm achieves superior performance, with a maximum power point tracking efficiency of 99.7 % compared to 99.64 % for CSO. Additionally, HOA exhibits a significantly faster settling time of 0.0570 s, outperforming CSO's 0.12 s, and maintains comparable rise times (<span><math><mrow><mn>0</mn><mo>.</mo><mn>0016</mn><mi>s</mi></mrow></math></span>) while eliminating voltage and current oscillations. Under varying thermal and pressure conditions, HOA demonstrates exceptional robustness, rapid convergence, and high stability, maintaining optimal power delivery where conventional methods degrade. This work represents the first successful integration of the Horse Herd Optimization Algorithm into MPPT control for PEM fuel cells and demonstrates its superiority over both traditional and intelligent techniques. It offers a highly efficient and adaptive solution, with promising prospects for future scalability and deployment in real-world fuel cell energy management systems.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108999"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of energy cooperatives in Ukraine: scale, energy mix and business models","authors":"Uliana Pysmenna ,&nbsp;Sviatoslav Petrovets ,&nbsp;Iryna Sotnyk ,&nbsp;Tetiana Kurbatova","doi":"10.1016/j.egyr.2025.108965","DOIUrl":"10.1016/j.egyr.2025.108965","url":null,"abstract":"<div><div>The paper explores the prerequisites for the expansion of energy cooperatives as a market-based form evolutioning from self-sufficiency of electricity supply to the wide range of models of the energy and energy-related business activity, basing on the international and Ukrainian experience. We assume that a cooperative size and energy technologies combination are important parameters that determine their efficiency. The insufficient per capita household income as the barrier of the energy cooperatives development hinders the development of sustainable energy and market transitions. To provide the investments that are able to cover the cost of purchasing and installing of generating units for self-sufficiency and active consumption, it is needed to align the share contribution and the needed installed generation capacity sufficient for the number of participants united with the appropriate amount of the share contribution and to define the optimal cooperative size. Maintaining the individual interest for each participant creates a driving force for increasing the number of energy cooperatives.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108965"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ship operational data driven fuel efficiency assessment for shaft generator using input convex neural network","authors":"Daehyuk Kim ,&nbsp;SoonSik Jang ,&nbsp;Jung-il Lee ,&nbsp;Shin Hyung Rhee ,&nbsp;Hyukchan Kwon ,&nbsp;Hyunhak Jeong","doi":"10.1016/j.egyr.2025.108993","DOIUrl":"10.1016/j.egyr.2025.108993","url":null,"abstract":"<div><div>This study develops a data-driven yet physically consistent framework to quantify the real-world fuel efficiency of a PTO-mode shaft generator (S/G) using high-resolution operational data from an 86k CBM LPG carrier. To capture the nonlinear and load-dependent interactions between propulsion and electric power generation, an Input Convex Neural Network (ICNN) is trained under convexity and monotonicity constraints in the S/G power ratio, ensuring both accurate prediction and physically reliable response shapes. Compared with conventional machine-learning models (MLP, gradient boosting, random forest), the ICNN achieves comparable predictive accuracy while eliminating the shape violations frequently observed in unconstrained models. Model performance remains high for both laden and ballast operations (R² = 0.88 – 0.94; RMSE ≈ 1 – 3 g/kWh). On-manifold partial dependence analysis reveals distinct operational patterns: in laden voyages, fuel savings emerge primarily above ∼ 60 % S/G power ratio, reaching ∼3.8 g/kWh at full utilization, whereas in ballast voyages savings increase monotonically across the entire range, peaking at ∼1.65 g/kWh. These behaviors align with main engine BSFC maps and reflect condition-dependent trade-offs between propulsion loading and auxiliary generator displacement. The proposed framework provides actionable guidelines, maximizing S/G use in ballast runs and selectively increasing it in laden runs, and offers a robust foundation for AI-assisted energy-management systems that optimize fuel economy under realistic operating constraints.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108993"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable and adaptive injection-production control in reservoirs via a multi-agent reinforcement learning approach","authors":"Shuang Zhao ,&nbsp;Chengcheng Liu ,&nbsp;Ji Ma","doi":"10.1016/j.egyr.2025.108983","DOIUrl":"10.1016/j.egyr.2025.108983","url":null,"abstract":"<div><div>The growing global energy demand necessitates more efficient reservoir management, highlighting the need for advanced injection-production optimization strategies. Traditional methods are computationally expensive and scale poorly, especially when new wells are added and nearby agents must be retrained. These limitations hinder their application in large, heterogeneous reservoirs and reduce their effectiveness for adaptive decision-making. To address these challenges, this study introduces an enhanced multi-agent reinforcement learning (MARL) framework with three key innovations. First, an online-updating surrogate model, based on a simplified U-Net architecture, partially replaces costly numerical simulations, significantly reducing computational overhead. Second, a regional observation construction method encodes relative well positions to capture inter-well dependencies and enhance local decision-making. Third, a self-adaptive, graph-based unified agent design eliminates the need for retraining when new wells are added, ensuring scalability. The proposed framework was validated using both a synthetic “Three-Channel” model and a real oilfield case. Experimental results show substantial improvements in displacement efficiency, delayed water breakthrough, and increased Net Present Value (NPV). Additionally, the framework adapts seamlessly to the addition of new wells without retraining, maintaining high computational efficiency. These results underscore the practical potential of the MARL-based approach as a robust and flexible solution for real-time reservoir management in dynamically evolving oil fields.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108983"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Renewable energy in EU agribusiness: Review of progress in meeting 2030 renewable energy directive III targets","authors":"Kacper Mańkowski ,&nbsp;Bartłomiej Bajan ,&nbsp;Aldona Mrówczyńska-Kamińska","doi":"10.1016/j.egyr.2025.109031","DOIUrl":"10.1016/j.egyr.2025.109031","url":null,"abstract":"<div><div>The European Union’s (EU) renewable energy targets for 2030 require a substantial acceleration in the adoption of renewable energy sources (RES) across all sectors. While macro-level progress has been notable, agriculture and agribusiness continue to lag in RES integration, thereby slowing down the overall pace of the energy transition. This study presents the first EU-wide assessment of RES uptake in these sectors, using an input–output model informed by RES targets extracted from the updated 2023 National Energy and Climate Plans (NECPs), prepared under the Renewable Energy Directive III (RED III). Unlike previous studies based on outdated RED II assumptions, this analysis reflects the revised 2023 policy landscape, providing a timely and policy-relevant perspective. Convergence toward the 42.5 % RES target was estimated using two historical trends: 2014–2022 and 2018–2022. Under the first trend, the overall economy is projected to reach the target by 2045, with agribusiness and agriculture lagging by 6 and 27 years, respectively. Under the second, more recent trend, convergence could occur by 2040 for the overall economy, with delays of 7 years for agribusiness and 21 years for agriculture. Although the 2030 RES target appears achievable at the aggregate level, deep structural disparities persist. Accelerating the transition in lagging sectors will require targeted incentives, investments in decentralized energy systems, and geographically differentiated policies aligned with national and regional resource conditions. These findings indicate that strengthened rural investment frameworks in biogas or the electrification of farm machinery could help close the sectoral gaps in RES adoption.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 109031"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding water management and cathode performance in LT-PEMFCs via EIS and DRT diagnostics","authors":"Emilija Todorovski ,&nbsp;Filip Todorovski ,&nbsp;Mihael Sekavčnik ,&nbsp;Mitja Mori ,&nbsp;Blaž Likozar ,&nbsp;Andrej Lotrič","doi":"10.1016/j.egyr.2025.109024","DOIUrl":"10.1016/j.egyr.2025.109024","url":null,"abstract":"<div><div>Low-Temperature Proton Exchange Membrane Fuel Cells (LT-PEMFCs) are key to sustainable energy technologies, but their performance is highly dependent on cathode operating conditions and membrane hydration. This study employs Electrochemical Impedance Spectroscopy (EIS) and the Distribution of Relaxation Times (DRT) to analyze the effects of cathode stoichiometry, temperature, cathode feed composition, and hydration levels on key electrochemical processes. The findings highlight the impact of operational parameters on oxygen reduction reaction (ORR) kinetics, proton transport, and mass transport resistance. DRT analysis identifies flooding and membrane drying as dominant performance-limiting phenomena. Pure oxygen feed mitigates mass transport limitations, while variations in air stoichiometry and temperature influence charge transfer resistance and proton conductivity. This study enhances understanding of LT-PEMFC behavior under diverse conditions and provides insights for optimizing performance and durability. The results provide diagnostic features and fundamental insights that can guide the development of future diagnostic frameworks for improved fuel cell control, enhanced water management strategies, and long-term operational stability.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 109024"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon price interval prediction by bidirectional long short-term memory and multi-objective optimization with an asymmetric scaling approach","authors":"Di Sha ,&nbsp;Arne Johannssen ,&nbsp;Xianyi Zeng ,&nbsp;Zhenglei He ,&nbsp;Hanhan Wu ,&nbsp;Kim Phuc Tran","doi":"10.1016/j.egyr.2025.108989","DOIUrl":"10.1016/j.egyr.2025.108989","url":null,"abstract":"<div><div>Accurate carbon price prediction is essential for decision-making and risk management. Most existing predictive models produce deterministic results and fail to account for uncertainties in carbon prices. To address this limitation, this study introduces an interval prediction framework that effectively captures uncertainties and enhances predictive performance. The proposed framework integrates eXtreme Gradient Boosting (XGBoost) for feature selection, a Modified Scaling Approach (MSA) to generate asymmetric prediction intervals and an improved Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) to determine the optimal scaling parameters. Finally, a Bidirectional Long Short-Term Memory (BiLSTM) network is employed to generate the final interval prediction results. Experiments show that the presented framework outperforms benchmark models and demonstrates robustness.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108989"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing household water heating practices in West Africa: Survey insights from Ouagadougou and Lomé","authors":"Kokouvi Edem N’Tsoukpoe ,&nbsp;Nahoua Soro ,&nbsp;Claude Sara Lekombo ,&nbsp;Eyram Kankoé Théophile Amovin-Assagba","doi":"10.1016/j.egyr.2025.108971","DOIUrl":"10.1016/j.egyr.2025.108971","url":null,"abstract":"<div><div>Hot water provision in West African households remains heavily dependent on polluting biomass and fossil fuels, exacerbating environmental degradation and health challenges. This study presents the first large-scale comparative analysis of water heating practices and the potential for solar water heater (SWH) adoption in two major cities with contrasting policy environments: Ouagadougou, Burkina Faso, and Lomé, Togo. A comprehensive survey of 1011 households in Ouagadougou and 765 in Lomé was conducted via face-to-face interviews. Results reveal stark divergences driven primarily by policy. In Ouagadougou, substantial LPG subsidies and SWH promotion have led to LPG being the dominant energy source (70 % of households) and a relatively high SWH adoption rate (9 %). In contrast, Lomé’s lack of incentives results in heavy reliance on charcoal (62 %) and a very low SWH adoption rate (0.4 %), despite a high expressed willingness to adopt (84 %). Bivariate analysis reveals that willingness to adopt is strongly associated with higher education levels and the use of modern energy sources. While economic savings and convenience are the primary motivators, environmental concerns play a secondary, though significant, role when prompted. Despite high user satisfaction (80 %), technical failures—particularly float malfunctions affecting 30 % of systems—and high upfront costs remain critical barriers. The findings underscore that targeted policy interventions are the primary catalyst for shifting household energy practices. We conclude that promoting SWHs in West Africa requires financial mechanisms to overcome initial costs, stringent quality assurance to ensure reliability, and awareness campaigns that bundle economic, practical, and environmental benefits.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108971"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geopolitical risks and the global renewable energy transition: Implications for energy security and economic resilience","authors":"Yi Li ,&nbsp;Muhammad Wasif Hanif ,&nbsp;Menghao Wen ,&nbsp;Abdul Khalique Khoso ,&nbsp;Wali Muhammad Khoso","doi":"10.1016/j.egyr.2025.12.012","DOIUrl":"10.1016/j.egyr.2025.12.012","url":null,"abstract":"<div><div>This study investigates the impact of geopolitical risks (GPR) on the global transition to renewable energy (RE) and its implications for energy security (ES), with a focus on the differential effects across advanced, developing, and least-developed economies. Using panel quantile regression, we analyze data from 94 countries (2002–2023) to uncover non-linear effects and assess moderation by economic and institutional factors. The results show that geopolitical risks accelerate RE adoption in advanced economies, while hindering progress in developing economies due to institutional and financial constraints. In least-developed economies, energy dependence exacerbates the negative impacts of geopolitical risks. Gross domestic product per capita and political stability. These findings provide insights into the diverse pathways shaped by geopolitical risks, highlighting the need for tailored policies that address the specific challenges and opportunities at different stages of energy dependence. This study emphasizes the importance of economic resilience and institutional capacity in navigating the geopolitical risks influencing global energy transitions.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108875"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrodynamic investigation of mooring-hinged, multi-floater offshore floating photovoltaic platform in irregular waves and wind","authors":"Ruijia Jin ,&nbsp;Tingting Zhu ,&nbsp;Baolei Geng ,&nbsp;Jining Song","doi":"10.1016/j.egyr.2025.11.083","DOIUrl":"10.1016/j.egyr.2025.11.083","url":null,"abstract":"<div><div>The floating photovoltaic (FPV) power generation technology in water had made up for some of the shortcomings of traditional land-based photovoltaics and has developed rapidly in the past decade. In order to obtain a deeper understanding of the hydrodynamic response of offshore floating photovoltaic (OFPV) under wind and wave conditions, the article used ANSYS-AQWA for a mooring hinged multi-floater OFPV platform in waves and wind based on the potential flow theory. The comparisons of motion responses of each module between only wave action and wave &amp; wind action were carried out to investigate the overall hydrodynamic characteristics. Unlike traditional FPV calculations, which were typically limited to hydrodynamic analysis, this paper further quantitatively evaluated the influence of wind loads on both the amplitude and frequency of structural motion responses. The results demonstrated the necessity and significance of incorporating wind load analysis in such structural assessments. At the same time, the influence of hinge damping on the motion response was also calculated here. The conclusions drawn from this study provide valuable guidance for the design and optimization of multi-floater FPV systems.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"15 ","pages":"Article 108824"},"PeriodicalIF":5.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145735781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}