Cleaner Energy Systems最新文献

{"title":"Machine learning-based prediction model of wind turbine power generation","authors":"Zaid Allal ,&nbsp;Hassan N. Noura ,&nbsp;Ola Salman ,&nbsp;Khaled Chahine","doi":"10.1016/j.cles.2025.100218","DOIUrl":"10.1016/j.cles.2025.100218","url":null,"abstract":"<div><div>Renewable energy sources have become central to the transition toward cleaner energy systems, with wind energy demonstrating the most rapid global growth since 1990. However, its production is inherently dependent on variable and uncontrollable factors such as weather conditions and wind dynamics. In this work, we analyze a dataset spanning two and a half years, collected from wind turbines, and apply extensive exploratory data analysis and preprocessing to enable accurate forecasting of wind power generation. Initially, the dataset was evaluated using multiple regression models for baseline predictions, while the Prophet model was employed to extract long-term trends and seasonality. The processed data were then integrated and used as input for CatBoost and Random Forest models, incorporating a windowing mechanism informed by autocorrelation and partial autocorrelation analysis to optimize temporal dependencies. Forecasting was conducted across three horizons: 15 min, 1 day, and 1 week ahead. The proposed hybrid approach achieved a root mean square error of 30.6 for 15 min forecasting, 50 for one-day forecasting, and 41 for one-week forecasting, representing at least a 50% improvement over the best standalone regression. Results further confirm the expected trend that longer forecasting horizons increase RMSE and reduce <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>, due to resampling constraints and the need for more extensive input data. Nonetheless, the hybrid methodology consistently outperformed standalone models, demonstrating stability and robustness across different horizons. By leveraging the complementary strengths of multiple regressors within a unified framework, this study highlights the potential of hybrid machine learning approaches to significantly enhance the predictive accuracy of wind energy forecasting.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100218"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145570935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal multi-objective design of a Photovoltaic/Battery/Wind hybrid system by implementing an innovative meta-heuristic algorithm","authors":"Pascalin Tiam Kapen","doi":"10.1016/j.cles.2025.100202","DOIUrl":"10.1016/j.cles.2025.100202","url":null,"abstract":"<div><div>Advancing optimization methodologies is crucial for addressing the complex challenges of real-world energy systems, particularly those involving high-dimensional search spaces. This work introduces the Caracal Optimization Algorithm (CAO), a novel metaheuristic inspired by the hunting behavior of caracals, known for their precision, agility, and adaptability. By mimicking the caracal's stealthy stalking, explosive leaps, and dynamic adjustments to prey movement, the algorithm incorporates chaotic exploration mechanisms and adaptive leap strategies, effectively balancing global search diversity and local solution refinement. This innovation enables the CAO to navigate intricate solution landscapes, avoid local optima, and achieve rapid convergence. The CAO was applied to optimize the sizing of off-grid hybrid energy systems, particularly Wind/Photovoltaic/Battery configurations, focusing on key metrics such as loss of power supply probability (LPSP), net present cost (NPC), and levelized cost of energy (LCOE). The algorithm was benchmarked against four established metaheuristic methods, Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Particle Swarm Optimization (PSO). Comparative analyses showed that CAO outperforms these benchmarks, achieving the best solution quality, faster convergence, and significantly reduced computational time. Notably, CAO reduced the LCOE to 0.1069 US$/kWh, the NPC to approximately US$ 50,874, and demonstrated superior energy cost optimization with faster convergence compared to other algorithms. The findings also highlighted significant variability in photovoltaic power output, peaking at 20 kW during high solar radiation, reflecting the intermittent nature of solar energy. Wind turbine power showed more consistency, peaking at 12 kW. Battery charging and discharging exhibited fluctuations based on weather, time of day, and seasonal changes. The analysis revealed that lower LCOE values occur under favorable financial conditions, such as low inflation and interest rates. Conversely, higher LCOE values were observed with increased inflation and interest rates, emphasizing the need for minimizing these financial factors for cost-effective energy generation. These results underline the Caracal Optimization Algorithm's potential to enhance hybrid renewable energy systems, offering a cleaner, more cost-effective solution. This study not only demonstrates the effectiveness of CAO in optimizing energy systems but also highlights its adaptability in addressing complex, multi-objective optimization problems, proving its capability to navigate high-dimensional spaces efficiently.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100202"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From policy to practice: Upper bound cost estimates of Europe ’s green hydrogen ambitions","authors":"Erlend Hordvei ,&nbsp;Sebastian Emil Hummelen ,&nbsp;Marianne Petersen ,&nbsp;Stian Backe ,&nbsp;Pedro Crespo del Granado","doi":"10.1016/j.cles.2025.100206","DOIUrl":"10.1016/j.cles.2025.100206","url":null,"abstract":"<div><div>As the European countries strive to meet their ambitious climate goals, renewable hydrogen has emerged to aid in decarbonizing energy-intensive sectors and support the overall energy transition. To ensure that hydrogen production aligns with these goals, the European Commission has introduced criteria for additionality, temporal correlation, and geographical correlation. These criteria are designed to ensure that hydrogen production from renewable sources supports the growth of renewable energy. This study assesses the impact of these criteria on green hydrogen production, focusing on production costs and technology impacts. The European energy market is simulated up to 2048 using stochastic programming, applying these requirements exclusively to green hydrogen production without the phased-in compliance period outlined in the EU regulations. The findings show that meeting the criteria will increase expected system costs by €82 billion from 2024 to 2048, largely due to the rapid shift from fossil fuels to renewable energy. The additionality requirement, which mandates the use of new renewable energy installations for electrolysis, proves to be the most expensive, but also the most effective in accelerating renewable energy adoption.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100206"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Small-scale biomass combined heat and power systems in remote indigenous communities: Economic, social and environmental sustainability challenges amid policy misalignment","authors":"Christoph Schilling ,&nbsp;Sheng H. Xie ,&nbsp;Blas Mola-Yudego ,&nbsp;Hisham Zerriffi ,&nbsp;Christopher Gaston ,&nbsp;Dominik Roeser","doi":"10.1016/j.cles.2025.100201","DOIUrl":"10.1016/j.cles.2025.100201","url":null,"abstract":"<div><div>This study evaluates the sustainability impacts of small-scale biomass combined heat and power (CHP) systems in remote communities, focusing on the case of Kwadacha, a remote Indigenous community in British Columbia. The analysis compares the biomass CHP system implemented in 2016 with the community’s previous diesel power and propane heating systems, examining economic, social, and environmental dimensions while exploring the factors that led to the project’s cessation in 2021.</div><div>The biomass CHP system demonstrated a 5.15-fold increase in local employment, a 2.76-fold rise in community income, and an annual greenhouse gas emissions avoidance of 1113 tCO₂e. It also achieved a notable supply chain cost advantage, with the cost of biomass transport and processing being approximately one-third that of diesel and propane delivery. However, high operational costs, escalating maintenance issues, and persistent labor shortages posed major barriers to long-term viability. These challenges were compounded by entrenched diesel subsidies, which created economic disincentives for renewable energy adoption despite clear sustainability gains.</div><div>The findings highlight the potential of biomass CHP systems to contribute to wildfire mitigation, rural economic development, and decarbonization in forested, off-grid communities. However, realizing these benefits requires policy realignment, sustained technical support, and integrated funding mechanisms. The Kwadacha project provides critical lessons for future deployments, emphasizing the need for context-specific strategies that balance economic, environmental, and social goals in the implementation of renewable energy systems.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100201"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy storage supply chain modeling and optimization: A systematic review","authors":"Dalal Bamufleh ,&nbsp;Yong Wang ,&nbsp;A. Rammohan ,&nbsp;Tao Yang","doi":"10.1016/j.cles.2025.100200","DOIUrl":"10.1016/j.cles.2025.100200","url":null,"abstract":"<div><div>This paper provides a comprehensive review of Energy Storage System (ESS) supply chain modeling and optimization over the past decade (2014–2024). Motivated by the increasing demand for ESS integration with renewable energy sources and the complexities of battery energy storage systems (BESSs), this study employs a systematic literature review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The review results indicated that multi-objective optimization models dominate ESS and BESS supply chain studies, due to their capability to manage the trade-offs between these chains' economic performance, environmental sustainability, and operational efficiency. The analysis identifies China's dominance in ESS research because of the Chinese government's extensive investments in renewable energy and electric vehicle (EV) production and characterizes 2019 as the most productive year for publications, given the global legislative changes and technological advancements. The review recognizes the future direction of ESS research related to integrating multiple optimization techniques, optimizing ESS supply chain environmental impacts, hybrid renewable ESSs, and shared ESSs. Also, it emphasizes the growing significance of artificial intelligence (AI), machine learning (ML), and deep reinforcement learning (DRL), as emerging methodologies for improving ESS supply chain optimization. This review paper contributes to the literature by providing practical insights related to ESS supply chain optimization, aligning with global decarbonization targets, and highlighting ESSs' future research approaches. Policymakers, manufacturers, energy providers, and researchers can utilize these findings to design sustainable ESS supply chains that optimize costs, environmental impacts, and social aspects.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100200"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144595825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uptake of solar energy by industries in Bangladesh: Driving factors, barriers, and opportunities","authors":"Nayma Akther Jahan,&nbsp;Shahana Afrose Chowdhury,&nbsp;Haseeb Md. Irfanullah,&nbsp;Samiya Ahmed Selim","doi":"10.1016/j.cles.2025.100205","DOIUrl":"10.1016/j.cles.2025.100205","url":null,"abstract":"<div><div>Bangladesh requires a huge amount of energy to keep its industries growing by using traditional fossil fuel options. The country has a huge potential for the rooftop solar PV systems (RSS) given its geographical location in the subtropical region, but the uptake of the RSS has not been satisfactory compared with the opportunity. There are studies on the potential rooftop area for installing the RSS, but no studies on the industries of Bangladesh from a user perspective. The present research identified the drivers and barriers to the RSS installation by interviewing representatives of different industries and using the technological acceptance model (TAM). It revealed that the emergence of the OPEX (operational expenditure) model, cost-effectiveness, energy security, and environmental awareness has driven the uptake of the RSS, whereas the upfront cost, bureaucracy, structural barrier, lack of information, and lack of financial incentives have demotivated the installation of the RSS. Financial incentives through policy adjustment, awareness building, and presenting best cases are recommended to motivate industries to adopt the RSS on a large scale.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100205"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential of renewable energy technologies for rural electrification in Southeast Asia: A review","authors":"Rizalman Mamat ,&nbsp;Mohd Fairusham Ghazali ,&nbsp;Erdiwansyah ,&nbsp;S.M. Rosdi","doi":"10.1016/j.cles.2025.100207","DOIUrl":"10.1016/j.cles.2025.100207","url":null,"abstract":"<div><div>Rural electrification remains a significant development challenge in Southeast Asia, where over 45 million people still lack access to reliable electricity. This review uses a comparative analysis of empirical data and policy interventions across the region to evaluate the potential and barriers of renewable energy technologies (RETs) including solar, wind, biomass, and small-scale hydropower. The study aims to synthesize regional implementation outcomes, identify enabling frameworks, and highlight scalable hybrid solutions. Methodologically, over 100 published sources were reviewed to extract quantitative and qualitative data from key case studies in countries such as Vietnam, Indonesia, and the Philippines. Results show that solar PV systems, with a cost decline exceeding 80 % in the past decade, represent the most viable off-grid solution. Vietnam will achieve over 16 GW of installed capacity by 2022. Biomass energy contributes up to 15 % of rural energy use in Indonesia and Thailand, while small hydropower accounts for 20 % of rural generation in Laos and Vietnam. Hybrid renewable energy systems (HRES), integrating solar, wind, and biomass, reduce costs by up to 30 % compared to standalone systems and enhance supply reliability. However, deployment remains hindered by upfront costs (e.g., over $2500 per household for solar), limited technical expertise, policy inconsistencies, and socio-cultural resistance. The novelty of this review lies in its regional synthesis of RET policy impacts and its proposal of a diagnostic framework linking technology choice with socio-economic conditions. In conclusion, targeted subsidies, capacity-building, and community-driven models are crucial to overcoming barriers and unlocking RET's potential for inclusive, resilient, and sustainable rural electrification in Southeast Asia.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100207"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Closed-loop workflow for short-term optimization of wind-powered reservoir management","authors":"Mathias M. Nilsen ,&nbsp;Rolf J. Lorentzen ,&nbsp;Olwijn Leeuwenburgh ,&nbsp;Andreas S. Stordal ,&nbsp;Eduardo Barros","doi":"10.1016/j.cles.2025.100213","DOIUrl":"10.1016/j.cles.2025.100213","url":null,"abstract":"<div><div>This paper presents a closed-loop workflow for short-term optimization of reservoir management powered by offshore wind energy. Motivated by the need to reduce CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions in the Norwegian oil and gas sector, the workflow integrates wind power forecasts into optimization of daily well control while adhering to a long-term production strategy optimized for economic output. The workflow utilizes coarsened reservoir models calibrated through ensemble-based data assimilation to minimize computational costs. A realistic benchmark model, Drogon, is used to demonstrate the methodology. The workflow dynamically adjusts well rates to align power demand with wind availability, minimizing reliance on gas turbines and thereby reducing emissions. The numerical experiment demonstrates the potential of the workflow by significantly reducing short-term emissions without compromising the NPV.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100213"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing phase change material placement in sustainable building envelopes for enhanced thermal performance","authors":"Azzeddine Elghomari,&nbsp;Amine Tilioua","doi":"10.1016/j.cles.2025.100220","DOIUrl":"10.1016/j.cles.2025.100220","url":null,"abstract":"<div><div>This study examines the thermal performance of cement-polystyrene walls, both with and without Phase Change Material (PCM), using a scaled-down thermal cavity with interchangeable sidewalls. The primary objective is to optimize the PCM layer placement within the wall structure by analyzing changes in surface temperature and reductions in heat flux. The results reveal that positioning the PCM layer next to the heat source maximizes latent heat release, thereby improving thermal regulation. Various factors, including the phase transition temperature, heat source temperature, and heat flux density, were taken into account. Experiments conducted at 45 °C, which represents typical summer conditions in the Drâa-Tafilalet Region in south-east Morocco, show that walls enhanced with phase change materials (PCMs) effectively reduce both surface heat flux and temperature. This study underscores the potential of incorporating PCM-enhanced cement-polystyrene walls to enhance thermal performance and energy efficiency in building materials.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100220"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Negative emission strategies to reduce the carbon intensity of Brazilian sugarcane ethanol under RenovaBio","authors":"Lucas G. Pereira ,&nbsp;Marília Ieda da S. Folegatti ,&nbsp;Nilza Patrícia Ramos ,&nbsp;Cristiano Alberto de Andrade ,&nbsp;Anna Leticia M.T. Pighinelli ,&nbsp;Rosana Galindo ,&nbsp;Joaquim E.A. Seabra","doi":"10.1016/j.cles.2025.100208","DOIUrl":"10.1016/j.cles.2025.100208","url":null,"abstract":"<div><div>Brazil’s National Biofuel Policy (RenovaBio) promotes negative emission technologies (NETs) as one of the instruments to reduce the carbon intensity (CI) of biofuels; however, no mill in the country has integrated such strategies into its production processes to date.</div><div>The present study examined the potential impact of two promising NETs (i.e, bioenergy with carbon capture and storage (BECCS) and field application of biochar) on the CI of sugarcane ethanol, calculated using the methodological approach adopted by RenovaBio. In addition, the assessment used data from the agricultural and industrial stages provided by 62 certified sugarcane mills.</div><div>Results show that these strategies have the potential to significantly reduce the CI of ethanol. The obtained value of +32.8 g CO₂e/MJ of hydrated ethanol (without NETs considered) could be reduced to +15.9 (with the application of 1.0 t biochar/ha), +10.4 (with BECCS from fermentation), and −81.3 (with BECCS from combustion). Ethanol-blended gasoline (produced in association with NETs) has the potential to reduce impacts; however, achieving reductions similar to those of electric and all-ethanol vehicles, when compared to conventional gasoline, would depend on NETs that are unlikely to be implemented (e.g. BECCS from combustion). Estimates show that the carbon credits made available in RenovaBio will probably not be sufficient to provide attractive financial viability. Other instruments, such as private funding through the voluntary carbon market (VCM) and specific national incentive policies, may be essential for financing NETs.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100208"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144861116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}