Cleaner Energy Systems最新文献

{"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":"2025-07-22","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":"Sustainability analysis of hybrid renewable-based power generation with battery energy storage system for remote islands: Application to Koh Hang, Thailand","authors":"Weerasak Chaichan ,&nbsp;Jompob Waewsak ,&nbsp;Yoawapa Naklua ,&nbsp;Fida Ali ,&nbsp;Chokchai Mueanmas ,&nbsp;Ruamporn Nikhom ,&nbsp;Chuleerat Kongruang ,&nbsp;Yves Gagnon","doi":"10.1016/j.cles.2025.100203","DOIUrl":"10.1016/j.cles.2025.100203","url":null,"abstract":"<div><div>This study focuses on the development of a hybrid renewable energy system, with a battery energy storage system, for a small island, Koh Hang, off the coast of Krabi province, in the Andaman Sea of Thailand. Currently un-powered, the island has a good solar energy potential, but limited wind energy potential. Using HOMER Pro optimization model, seven hybrid renewable energy systems consisting of solar PV, wind, biogas, and a battery energy storage system (BESS) are studied to identify the optimal configuration to meet the load demand with the lowest levelized cost of energy (LCOE). Among the hybrid configurations studied, the optimal solar PV – biogas - BESS system offered the lowest LCOE of 0.215 US$/kWh. A public opinion survey was also carried out in the community to measure the level of acceptance of such system on the island, with the willingness to pay for a proposed tariff being the key issue for the long-term sustainability of the proposed system. This work, which can be replicated in similar off-grid microgrids, contribute in improving the quality of life and the economy of off-grid settlements, while minimizing the impacts on the environment.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100203"},"PeriodicalIF":0.0,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704876","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":"2025-07-16","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":"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":"2025-07-15","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":"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":"2025-07-14","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":"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":"2025-07-05","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":"Advancing grid stability and renewable energy: Policy evolution of battery energy storage systems in China, Japan, and South Korea","authors":"Michael Osezua,&nbsp;Olusegun S. Tomomewo","doi":"10.1016/j.cles.2025.100199","DOIUrl":"10.1016/j.cles.2025.100199","url":null,"abstract":"<div><div>The evolution of policies and regulations supporting battery energy storage system (BESS) development, utilization, and sustainability to enhance resource adequacy was investigated. The study examined the role of BESS in mitigating renewable energy intermittency, using China, Japan, and South Korea as case studies. The review finds that environmental, economic, political, technological, and regulatory factors significantly influence BESS applications' viability, growth, and sustainability. BESS offers environmental and social benefits but faces challenges like raw material price volatility and supply chain disruptions. The study concludes that integrating renewable energy sources and the growing demand for grid stability will continue to drive BESS adoption. However, supply chain challenges, international green trade barriers, and evolving technologies will shape the next phase of BESS growth. Collaboration among stakeholders, strategic partnerships, technological innovation, and supportive policies are required to advance the global adoption of BESS. The study highlights critical policy frameworks facilitating BESS deployment while ensuring grid stability and sustainability.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100199"},"PeriodicalIF":0.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144595780","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":"Efficient Deep-Reinforcement Learning for Photovoltaic Systems Under Faults Based on the I-V Curve Approach","authors":"YETTOU Tariq ,&nbsp;SEGHIOUR Abdellatif ,&nbsp;BOUCHETATA Nadir ,&nbsp;BENOUZZA Noureddine ,&nbsp;MOSTEFAOUI Imene Meriem ,&nbsp;RABHI Abdelhamid ,&nbsp;Santiago Silvestre ,&nbsp;CHOUDER Aissa","doi":"10.1016/j.cles.2025.100197","DOIUrl":"10.1016/j.cles.2025.100197","url":null,"abstract":"<div><div>Cleaner and sustainable Photovoltaic (PV) systems need to be supervised and monitored to reduce waste energy and improve power efficiency. The proposed technique in this work enhances solar energy production by precise fault detection of short-circuit and partial shading. It extends the PV system lifespan by mitigation component and further premature replacements. Moreover, automatic fault diagnosis helps maintain steady performance in variable climatic conditions and under varying occurred faults that minimize the backup to generators and energy losses. Firstly, we introduce a Bonobo Optimization Algorithm (BOA) that is capable of extracting and identifying the unknown parameters of the PV cell to model our study PV system and to mimic the fault behaviors. The identified model is validated and then used to generate the I-V and P-V curves, which are then fed to three autoencoders (AE) within an unsupervised learning framework to extract their features. Afterward, reinforcement learning (RL) is integrated through a stacked autoencoder (SAE) to combine environmental attributes such as solar irradiance and temperature with electrical features to improve the learned features and their sparsity. Also, to enable the system to adapt dynamically to new fault scenarios and noisy environments, deep-reinforcement learning (DRL) improves feature representation and classification through Artificial Neural Networks (ANN). This methodology provides an identification and categorization of 12 selected fault types in separated and combined ways, where this technique has been applied to a PV plant located in Algeria. The classification results exhibited exceptional accuracy, achieving 100% in the training phase and 99.8% in the testing phase, even amongst noisy input conditions with 97.2%. This study provides valuable insights into improving the reliability and efficiency of PV systems, particularly in the smart IV diagnosis that used multi-string PV inverter.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100197"},"PeriodicalIF":0.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580310","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":"Providing electricity price information to households and reducing electricity consumption: Results from a field experiment in Japan","authors":"Kazuma Murakami ,&nbsp;Ikuho Kochi","doi":"10.1016/j.cles.2025.100195","DOIUrl":"10.1016/j.cles.2025.100195","url":null,"abstract":"<div><div>Electricity accounts for 65.3 % of household CO₂ emissions in Japan; therefore, more household energy conservation is needed. This study examines the effects of information provision on various household energy-saving behaviors using randomized controlled trials (RCT). For Japanese consumers who have recently become free to choose their electricity provider, we examine two types of information provision with the same economic incentives but different framing: <em>information on the Past -</em> information about historical changes in electricity bills for the average household of their electricity provider–and <em>information on Others -</em> information about differences in electricity bills for the average household of different electricity providers. We collected objective measures of household electricity consumption levels through meter readings and subjective measures of behavioral changes through a questionnaire. Our results show that <em>information on the Past</em> has more impact on reducing electricity consumption for households with a higher volume of electricity consumption than others. The channels for this reduction are the behaviors of “not leaving the air conditioner on,” a constant time-consuming behavior, and “lowering the refrigerator's internal temperature,” a hassle-free one-time behavior. <em>Information on the Past</em> can be a low-cost and proactive information-provision measure for non-profit organizations and local governments.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100195"},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518047","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":"Application of the distributed photovoltaic systems towards oil-gas field and its implications for carbon emission reduction in China: A review on current and novel perspective on engineering approaches","authors":"Jun Liu ,&nbsp;Shenghao Liu ,&nbsp;Mingxiang Li ,&nbsp;Xueying Wu ,&nbsp;Zhengwei Li ,&nbsp;Xia Hao","doi":"10.1016/j.cles.2025.100198","DOIUrl":"10.1016/j.cles.2025.100198","url":null,"abstract":"<div><div>In China, the current energy consumption and pollution levels of oilfield are not in line with green development trends. Consequently, it is essential to integrate traditional oil/gas exploitation with renewable energy, like photovoltaic power. This paper provides an overview of the application of Distributed Photovoltaic Systems (DPVS) in oil-gas field. China's escalating energy demand and environmental concerns have underscored the significance of renewable energy, particularly photovoltaics. It also addresses the environmental impact of oilfield extraction, highlighting the necessity to reduce CO₂ emissions. By analyzing policies that promote renewable energy, the paper identifies the DPVS potential in alleviating environmental issues. The paper examines the key elements and development status of photovoltaic systems for oil-gas fields, encompassing their history, components, and technologies. It explores the power consumption and system characteristics of oil-gas fields, proposing a structured methodology for designing and planning DPVS -including feasibility analysis, equipment selection, and cost calculations. Additionally, the paper assesses the economic benefits of DPVS using indicators such as Net Present Value, Internal Rate of Return, Dynamic Payback Period, and Levelized Cost of Energy. Finally, the paper discusses the limitations of DPVS in oilfields and outlines future trends, including solar-wind hybrid systems, DC microgrids, and integrated energy systems.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100198"},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557372","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}