Energy Reports最新文献_第4页

Wind farm parameter optimization identification method based on multi-agent SAC 基于多智能体SAC的风电场参数优化识别方法

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-13 DOI: 10.1016/j.egyr.2025.06.002

Qiu Quan Deng, Cui Yun Luo, Yin Wu, Guang Ming Li, Xie Jin Ling, Zhen Cheng Liang

引用次数: 0

A novel multi-objective approach to user-centric energy management systems 以用户为中心的能源管理系统的一种新的多目标方法

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-13 DOI: 10.1016/j.egyr.2025.05.084

Bahman Ahmadi , Gerwin Hoogsteen , Paweł Zawadzki , Marco E.T. Gerards , Weronika Radziszewska , Sebastian Bykuć , Johann L. Hurink

{"title":"A novel multi-objective approach to user-centric energy management systems","authors":"Bahman Ahmadi , Gerwin Hoogsteen , Paweł Zawadzki , Marco E.T. Gerards , Weronika Radziszewska , Sebastian Bykuć , Johann L. Hurink","doi":"10.1016/j.egyr.2025.05.084","DOIUrl":"10.1016/j.egyr.2025.05.084","url":null,"abstract":"<div><div>The growing complexity of micro-grid management and the demand for resilient, sustainable energy systems require solutions that go beyond traditional management strategies. This paper introduces a Multi-Objective Energy Management System (MOEMS) designed for micro-grids and energy communities, emphasizing resilience and sustainability. Unlike conventional Energy Management Systems (EMS), which mainly focus on cost and efficiency, MOEMS takes a user-centered approach. It incorporates a democratic decision-making process that involves all stakeholders, enabling personalized energy management tailored to user preferences and environmental considerations. MOEMS is used to address grid challenges like power congestion and voltage issues while balancing diverse stakeholder goals. The optimization problem is formulated as a mixed-integer non-linear program and adopted to be solved using a free and open-source solver. The proposed framework leverages the results of a multi-objective optimization model, allowing users to define their preferences. By specifying an acceptable solution space, the central controller in the micro-grid can optimize operations while ensuring that the selected solutions align with user expectations. The system is validated through simulations and a real-world micro-grid case study, demonstrating its adaptability to different setups. To evaluate its effectiveness, MOEMS is compared with traditional EMS approaches, including profile steering and methods that prioritize economic and environmental factors. A real-time implementation in the Kezo micro-grid further demonstrates its capability to dynamically manage energy flows, meet user energy demands, and adapt to real-time fluctuations in supply and demand. Significantly, MOEMS achieved up to 22% higher annual electricity cost savings and a 37% reduction in CO2 emissions compared to traditional EMS methods.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 185-204"},"PeriodicalIF":4.7,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280229","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}

引用次数: 0

Energy communities typologies and performances: Impact of members configurations, system size and management 能源社区的类型和性能：成员配置、系统规模和管理的影响

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-12 DOI: 10.1016/j.egyr.2025.05.049

Maria Victoria Gasca , Remy Rigo-Mariani , Vincent Debusschere , Yousra Sidqi

{"title":"Energy communities typologies and performances: Impact of members configurations, system size and management","authors":"Maria Victoria Gasca , Remy Rigo-Mariani , Vincent Debusschere , Yousra Sidqi","doi":"10.1016/j.egyr.2025.05.049","DOIUrl":"10.1016/j.egyr.2025.05.049","url":null,"abstract":"<div><div>Energy communities have gained significant interest in recent years as they enable active citizen participation in the energy transition. Most research in energy communities delves into strategies for enhancing sustainability, economic viability, and fairness. However, these strategies’ effectiveness largely depends on each energy community’s specific characteristics, including members types and available assets. This study focuses on understanding the impact of input parameters across different energy community typologies. It examines community size, the percentage of prosumers, and the diversity of members’ power profiles, analyzing 24,000 distinct configurations derived from an initial dataset of 92 load profiles. The study evaluates multiple setups for individual choices of solar photovoltaic systems and energy storage assets. The assessment applies a collective optimal management strategy to compare self-consumption and potential energy bill savings against a baseline where end-users operate individually. The same management strategy is applied consistently across various energy community typologies to demonstrate that the outcomes are primarily determined by the diversity of inputs (i.e., the energy community’s specific characteristics) rather than the energy management approach itself. The results indicate that energy communities with more than 20 members do not experience significant performance enhancements, regardless of operational choices. Additionally, the findings highlight that diversifying member types is more beneficial than oversizing the generation and storage asset capacity. Ultimately, the results exhibit that energy communities with a percentage of only consumers yield favorable outcomes for all members. Optimal configurations are identified when the composition comprises 75% of prosumers with heterogeneous load profiles.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 173-184"},"PeriodicalIF":4.7,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272626","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}

引用次数: 0

Regulatory-driven optimization of integrated energy systems: A legal and policy-compliant framework for flexibility and carbon management 法规驱动的综合能源系统优化：一个符合法律和政策的灵活性和碳管理框架

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-11 DOI: 10.1016/j.egyr.2025.05.048

Cynthia Xin Ding , Simona Zhong , Shuangqi Li , Mohannad Alhazmi

{"title":"Regulatory-driven optimization of integrated energy systems: A legal and policy-compliant framework for flexibility and carbon management","authors":"Cynthia Xin Ding , Simona Zhong , Shuangqi Li , Mohannad Alhazmi","doi":"10.1016/j.egyr.2025.05.048","DOIUrl":"10.1016/j.egyr.2025.05.048","url":null,"abstract":"<div><div>This paper develops a technically rigorous optimization framework for regulatory-compliant dispatch in integrated power systems operating under complex carbon market structures, with specific emphasis on California’s cap-and-trade regime and demand-side policy instruments. A hierarchical bilevel optimization model is constructed, wherein the upper level represents the policy authority setting dynamic emissions caps and DR incentive structures, while the lower level captures the optimal operation of multi-energy power systems — including electricity, thermal, and gas subsystems — subject to intertemporal unit commitment, network constraints, and compliance penalties. To address deep uncertainty in carbon pricing and market responses, the lower-level model embeds a Wasserstein-metric-based Distributionally Robust Optimization (DRO) formulation, ensuring operational resilience under ambiguous regulatory signals. Furthermore, a Non-dominated Sorting Genetic Algorithm III (NSGA-III) is employed to identify Pareto-efficient strategies balancing cost minimization, flexibility enhancement, and legal adherence. Numerical experiments on a testbed modeled after Kern County, California — comprising high-penetration renewables, battery storage, and flexible loads — demonstrate that the proposed framework can enhance nodal flexibility by 27%, reduce emissions penalties by 19%, and dynamically adjust dispatch strategies in response to fluctuating regulatory parameters. The results underscore the critical need for power systems to embed policy-awareness into optimization routines to achieve resilient and regulation-compliant operations under evolving carbon-constrained environments.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 157-172"},"PeriodicalIF":4.7,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264086","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}

引用次数: 0

Empirical assessment of life cycle GHG emissions of historical buildings with heritage values 具有遗产价值的历史建筑生命周期温室气体排放的实证评估

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-11 DOI: 10.1016/j.egyr.2025.05.073

Freja Nygaard Rasmussen , Troels Frey Andersen , Anne Mette Rahbæk , Harpa Birgisdóttir , Chiara Bertolin

{"title":"Empirical assessment of life cycle GHG emissions of historical buildings with heritage values","authors":"Freja Nygaard Rasmussen , Troels Frey Andersen , Anne Mette Rahbæk , Harpa Birgisdóttir , Chiara Bertolin","doi":"10.1016/j.egyr.2025.05.073","DOIUrl":"10.1016/j.egyr.2025.05.073","url":null,"abstract":"<div><div>Historic building stocks have important cultural and aesthetic values embedded in the designs and urban environments. Careful renovation, maintenance and management practices are needed to ensure that heritage values in historic buildings are not lost. However, there is little empirical evidence of the life cycle processes from renovation practices and the greenhouse gas emissions (GHGe) associated with them. This study presents a life cycle-based assessment of 56 historical buildings in Denmark. Results show GHGe in the range of 3–178 kg CO<sub>2</sub>eq/m<sup>2</sup> and a median of 66 kg CO<sub>2</sub>eq/m<sup>2</sup>. These numbers represent the production, construction waste treatment and final end-of-life modules of the building life cycle. Maintenance logs from the 56 case study buildings over a period from 2015 to 2023 provide unique insights into real maintenance-repair-replacement activities. These numbers show, in general, negligible GHGe to the overall result, although a few of the replacement activities show to be significant. Future logging and improved granularity in modelling between maintenance, repair and replacements could provide valuable insights for research and practice. Post-renovation median energy use for heating and hot water is found at 123 kWh/m<sup>2</sup>/year for residential- and 119 kWh/m<sup>2</sup>/year for non-residential buildings. The heating technology in place shows to be the most important determinant for the life cycle GHGe from the renovated buildings, pointing to the importance of effective energy management and energy use practices. The analysis of the results highlights the important dimensions of a building’s characteristics, condition, and transformative use as key elements in determining the GHGe from renovation activities.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 141-156"},"PeriodicalIF":4.7,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264085","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}

引用次数: 0

Green hydrogen in the Alps: Mapping local stakeholders perspectives and identifying opportunities for decarbonization 阿尔卑斯山的绿色氢：绘制当地利益相关者的观点并确定脱碳的机会

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-11 DOI: 10.1016/j.egyr.2025.06.001

Eleonora Cordioli, Jacopo de Maigret, Matteo Testi, Luigi Crema

{"title":"Green hydrogen in the Alps: Mapping local stakeholders perspectives and identifying opportunities for decarbonization","authors":"Eleonora Cordioli, Jacopo de Maigret, Matteo Testi, Luigi Crema","doi":"10.1016/j.egyr.2025.06.001","DOIUrl":"10.1016/j.egyr.2025.06.001","url":null,"abstract":"<div><div>The effects of climate change and reliance on fossil fuels in the Alps highlight the need for energy sufficiency, improved efficiency, and renewable energy deployment to support decarbonization goals. Hydrogen has gained attention as a versatile, zero-emission energy carrier with the potential to drive cleaner energy solutions and sustainable tourism in Alpine regions. This study shares findings from a hydrogen survey conducted within the Interreg Alpine Space AMETHyST project, which included questionnaires and roundtable discussions across Alpine territories. The survey explored hydrogen’s role in decarbonizing the Alps, gathering insights from local stakeholders about their knowledge, expertise, needs, and targets for hydrogen solutions. It also mapped existing hydrogen initiatives. Results revealed strong interest in hydrogen implementation, with many territories eager to launch projects. However, high investment and operational costs, along with associated risks, are key barriers. The absence of clear local hydrogen strategies and of a comprehensive regulatory framework also poses significant challenges. Incentivization schemes could facilitate initiatives and foster local hydrogen economies. The most promising application areas for hydrogen in the Alps are private and public mobility sectors. The residential sector, particularly in tourist accommodations, also presents potential. Regardless of specific uses, developing renewable energy capacity and infrastructure is essential to create green hydrogen ecosystems that can store excess renewable energy from intermittent sources for later use.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 128-140"},"PeriodicalIF":4.7,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254698","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}

引用次数: 0

Federated heterogeneous multi-agent deep reinforcement learning-based attack resilience scheduling for heterogeneous multi-integrated energy system 基于深度强化学习的联邦异构多智能体异构多集成能源系统攻击弹性调度

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-10 DOI: 10.1016/j.egyr.2025.05.085

Hainan Qi , Wenjie Ma , Bingsong Zhao

{"title":"Federated heterogeneous multi-agent deep reinforcement learning-based attack resilience scheduling for heterogeneous multi-integrated energy system","authors":"Hainan Qi , Wenjie Ma , Bingsong Zhao","doi":"10.1016/j.egyr.2025.05.085","DOIUrl":"10.1016/j.egyr.2025.05.085","url":null,"abstract":"<div><div>The increasing scale of heterogeneous multi-integrated energy system (MIES) exposes critical limitations in conventional scheduling methods, particularly regarding privacy preservation, coordination of heterogeneous systems, and resilience against cyberattacks. To address these challenges, this paper proposes a resilient scheduling framework based on federated heterogeneous multi-agent soft actor-critic (Fed-HMASAC), integrating federated learning (FL) and heterogeneous multi-agent deep reinforcement learning (HMADRL). Firstly, a heterogeneous MIES model incorporating multi-energy coupling and a dynamic price attack (DPA) mechanism is established. Furthermore, a federated heterogeneous multi-agent architecture is developed, which coordinates the collaboration of differentiated state/action space agents based on the advantage function decomposition, and proposes an adversarial training mechanism to enhance the resilience of the policy network against DPAs. The experimental results show that the proposed framework possesses better economic performance compared to the baseline approach while maintaining the stability of the scheduling strategies under continuous DPA conditions, and achieves data privacy preservation through FL.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 116-127"},"PeriodicalIF":4.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254697","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}

引用次数: 0

Generative AI applied for synthetic data in PMU 生成式人工智能应用于PMU的综合数据

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-10 DOI: 10.1016/j.egyr.2025.05.062

Felipe Proença de Albuquerque , Eduardo Coelho Marques da Costa , Luisa Helena Bartocci Liboni

{"title":"Generative AI applied for synthetic data in PMU","authors":"Felipe Proença de Albuquerque , Eduardo Coelho Marques da Costa , Luisa Helena Bartocci Liboni","doi":"10.1016/j.egyr.2025.05.062","DOIUrl":"10.1016/j.egyr.2025.05.062","url":null,"abstract":"<div><div>The growing deployment of Phasor Measurement Units (PMUs) has enhanced power system observability but introduced new challenges related to data privacy, incompleteness, and measurement quality. To address these issues, this paper proposes a data-driven methodology for generating and completing PMU phasor measurements using Generative Artificial Intelligence. Specifically, we employ Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) trained on real-world PMU datasets to learn the underlying empirical data distributions without assuming predefined statistical models. The proposed deep generative models are evaluated against traditional statistical techniques based on Gaussian Copulas using a suite of distributional similarity metrics, including Kullback–Leibler (KL) divergence, Hellinger distance, Maximum Deviation Nearest Neighbor (MDNN), and the Kolmogorov–Smirnov (KS) test. The GAN model achieved the best distributional fidelity, with KL divergence as low as 0.0106 and Hellinger distance of 0.0435 for voltage signals. In a synthetic data reconstruction task with 0.5% missing values, the GAN reduced the percentage root mean squared error (PRMSE) to 0.52% for voltage and 2.19% for current—significantly outperforming baseline methods. Moreover, the GAN was able to augment the dataset from 1489 to 5000 samples while preserving key statistical properties, as validated by empirical distribution tests. These results demonstrate that deep generative models not only offer superior accuracy but also provide statistically consistent synthetic PMU data, making them a robust alternative to conventional methods for enhancing power system datasets.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 103-115"},"PeriodicalIF":4.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241940","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}

引用次数: 0

Spatial multi-criteria play-based analysis for HT-ATES systems across the Swiss Molasse Plateau 瑞士Molasse高原HT-ATES系统的空间多标准游戏分析

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-09 DOI: 10.1016/j.egyr.2025.05.064

L. Guglielmetti , R. Lehu , A. Daniilidis , B. Valley , A. Moscariello

{"title":"Spatial multi-criteria play-based analysis for HT-ATES systems across the Swiss Molasse Plateau","authors":"L. Guglielmetti , R. Lehu , A. Daniilidis , B. Valley , A. Moscariello","doi":"10.1016/j.egyr.2025.05.064","DOIUrl":"10.1016/j.egyr.2025.05.064","url":null,"abstract":"<div><div>Energy storage plays a crucial role in decarbonizing the global energy system, particularly in the heating sector, which accounts for nearly 50 % of global energy demand. However, a significant challenge remains in balancing supply and demand from renewable energy sources. <strong>High-Temperature Aquifer Thermal Energy Storage (HT-ATES)</strong> presents a promising solution by enabling seasonal energy storage and shifting thermal loads efficiently. The successful implementation of HT-ATES requires a comprehensive understanding of both subsurface geological conditions and surface constraints to identify optimal storage sites. This study introduces a <strong>favorability assessment framework</strong> for HT-ATES systems across the <strong>Swiss Molasse Plateau (SMP)</strong>, utilizing <strong>spatial multi-criteria play-based analysis (SMCPBA)</strong>. Two key geological targets—the <strong>Cenozoic Molasse and Upper Mesozoic formations</strong>—are assessed alongside energy system criteria to pinpoint high-potential areas for future development. The findings highlight major urban centers such as <strong>Geneva, Lausanne, and Zurich</strong> as prime candidates due to their significant heat demand. However, broad-scale estimations necessitate <strong>higher-resolution data and site-specific feasibility studies</strong> for accurate assessment and implementation. The scalability of this methodology makes it applicable to various geographic contexts, supporting <strong>targeted pilot projects and feasibility assessments</strong>. Advancing HT-ATES technologies through refined methodologies and practical applications will contribute to Switzerland’s <strong>sustainable energy transition and long-term energy resilience</strong>.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 85-102"},"PeriodicalIF":4.7,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241939","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}

引用次数: 0

Machine learning-based predictive modelling of renewable energy adoption in developing countries 发展中国家可再生能源采用的基于机器学习的预测模型

IF 4.7 3区工程技术

Energy Reports Pub Date : 2025-06-07 DOI: 10.1016/j.egyr.2025.05.066

Williams Ossai, Temitayo Matthew Fagbola

{"title":"Machine learning-based predictive modelling of renewable energy adoption in developing countries","authors":"Williams Ossai, Temitayo Matthew Fagbola","doi":"10.1016/j.egyr.2025.05.066","DOIUrl":"10.1016/j.egyr.2025.05.066","url":null,"abstract":"<div><div>This study explores global renewable energy trends in alignment with the 2030 Sustainable Development Goals. Employing and fine-tuning the ExtraTreesRegressor, models were developed to predict adoption levels of electricity from solar, wind, hydro, and biomass sources. Strategic random search parameters were used to optimize the ExtraTreesRegressor. Evaluation based on Mean Square Error (MSE) and R-squared (R<sup>2</sup>) scores revealed that the ExtraTreesRegressor, outperformed other state-of-the-art regression models. Notably, the solar model exhibited commendable performance in test set evaluation (MSE: 0.4450, R<sup>2</sup>: 0.9849) and cross-validation (MSE: 4.3279, R<sup>2</sup>: 0.9079). Similarly, the wind model showed robust outcomes in both test set evaluation (MSE: 1.2233, R<sup>2</sup>: 0.9969) and cross-validation (MSE: 5.3136, R<sup>2</sup>: 0.9846). However, the hydro model faced nuanced challenges with test set evaluation (MSE: 33.3474, R<sup>2</sup>: 0.9960) and cross-validation (MSE: 20.4235, R2: 0.9961). The biomass model achieved notable results in test set evaluation (MSE: 0.3196, R<sup>2</sup>: 0.9960) and cross-validation (MSE: 0.5943, R<sup>2</sup>: 0.9901). Based on the findings from this study, GDP, non-renewable electricity consumption, and population size have been identified as key drivers of renewable energy adoption. Insights from this research will contribute to a deeper understanding of the intricate dynamics influencing renewable energy landscapes in developing countries.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 66-84"},"PeriodicalIF":4.7,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241938","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}

引用次数: 0