IF 9.4 1区工程技术

Energy Pub Date : 2025-10-04 DOI: 10.1016/j.energy.2025.138780

Tianyang Xia , Dapeng Sun , Tianchi Lin , Ming He , Yiming Li , Xingan Liu , Tianlai Li

{"title":"Study on winter climatic characteristics and temperature prediction model for solar greenhouses in cold regions","authors":"Tianyang Xia , Dapeng Sun , Tianchi Lin , Ming He , Yiming Li , Xingan Liu , Tianlai Li","doi":"10.1016/j.energy.2025.138780","DOIUrl":"10.1016/j.energy.2025.138780","url":null,"abstract":"<div><div>Solar greenhouses are essential for sustainable year-round crop production in cold regions; however, their thermal performance is significantly influenced by climatic uncertainties. Therefore, robust temperature prediction models are necessary to ensure optimal energy management. This study examines the winter climatic characteristics and develops temperature prediction models for solar greenhouses in cold regions. Hourly nighttime temperature prediction models for sunny, cloudy, and overcast conditions were developed using multiple linear regression and random forest regression, based on historical weather forecast data and field test measurements. The model calculates the future temperature of the greenhouse by inputting initial data on water and air temperature at a specific time, and by using future meteorological data covering outdoor temperature and humidity as well as surface wind speed. The results indicate that the multiple linear regression model exhibits reliable performance, with R<sup>2</sup> values of 0.71 for sunny days, 0.75 for cloudy days, and 0.82 for overcast days. In contrast, the random forest regression model demonstrates superior accuracy in more complex weather conditions, achieving R<sup>2</sup> values of 0.78 for sunny days and 0.81 for cloudy days. Key climatic factors, including outdoor temperature, relative humidity, and wind speed, exhibit distinct correlations with indoor temperature that vary depending on weather types, thereby influencing the selection of appropriate models. The most suitable prediction model can be selected based on the current weather conditions. The findings present a data-driven framework to optimize heat release strategies in solar water heating systems and improve the accuracy of greenhouse climate predictions.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138780"},"PeriodicalIF":9.4,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In-context learning for nano-PCM thermal behavior prediction in battery thermal management via Lattice Boltzmann simulation 基于晶格玻尔兹曼模拟的电池热管理中纳米pcm热行为预测的上下文学习

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-04 DOI: 10.1016/j.energy.2025.138693

Bichen Shang , Guo Li , Weijie Sun , Liwei Zhang , Guanzhe Cui , Jiyuan Tu , Xiang Fang , Xueren Li

{"title":"In-context learning for nano-PCM thermal behavior prediction in battery thermal management via Lattice Boltzmann simulation","authors":"Bichen Shang , Guo Li , Weijie Sun , Liwei Zhang , Guanzhe Cui , Jiyuan Tu , Xiang Fang , Xueren Li","doi":"10.1016/j.energy.2025.138693","DOIUrl":"10.1016/j.energy.2025.138693","url":null,"abstract":"<div><div>Effective thermal management is crucial for ensuring the safety and performance of lithium ion batteries in electric vehicles. While nano-enhanced phase change materials (nano-PCMs) offer excellent thermal regulation, their effectiveness is often limited by localized heat accumulation from natural convection. Existing ML-based studies mostly focus on temperature metrics alone, neglecting thermal uniformity and relying on black-box models with limited interpretability. This study proposed a zonal nanoparticle distribution strategy and utilized high-fidelity Lattice Boltzmann Method (LBM) simulations to investigate underlying heat transfer mechanisms in nano-enhanced PCM systems. The state-of-the-art Tabular Prior-data Fitted Network (TabPFN) was then employed to accurately predict key thermal indicators and was benchmarked against widely used models such as BPNNs, XGBoost, and CatBoost. Furthermore, SHapley Additive exPlanations (SHAP) analysis was applied to interpret TabPFN outputs, revealing key regional features and providing physical insights into system performance. The results demonstrated that with optimal non-uniform nanoparticle distribution pattern, the Nusselt number increased by 12.04 % and melting time was reduced by 13.05 %. TabPFN exhibited superior prediction accuracy compared to other popular machine learning models, with error bins generally lower in magnitude and reductions in MAE and RMSE by 8–92 % and 7–90 %. SHAP analysis further visualized quantitative correlation between training inputs and target variables and their influence on convective behavior and heat retention. The proposed explainable in-context learning framework based on TabPFN and SHAP is expected to provide valuable insights for guiding the design and optimization of advanced nano-PCM battery thermal management systems.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138693"},"PeriodicalIF":9.4,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-scenario state of charge adaptive estimation of lithium iron phosphate batteries based on impedance timescale information 基于阻抗时间尺度信息的磷酸铁锂电池多场景充电状态自适应估计

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-04 DOI: 10.1016/j.energy.2025.138745

Guangjun Qian , Zhicheng Zhu , Peng Guo , Lifang Liu , Yuedong Sun , Yuejiu Zheng , Xuebing Han , Minggao Ouyang

{"title":"Multi-scenario state of charge adaptive estimation of lithium iron phosphate batteries based on impedance timescale information","authors":"Guangjun Qian , Zhicheng Zhu , Peng Guo , Lifang Liu , Yuedong Sun , Yuejiu Zheng , Xuebing Han , Minggao Ouyang","doi":"10.1016/j.energy.2025.138745","DOIUrl":"10.1016/j.energy.2025.138745","url":null,"abstract":"<div><div>To address the state of charge (SOC) estimation challenge in lithium iron phosphate (LFP) batteries caused by the flat open-circuit voltage plateau, a multi-dimensional feature extraction method based on impedance timescale information (TI) is proposed. TI, derived from distribution of relaxation times analysis, spans 10<sup>−5</sup> s to several hundred seconds and reflects key dynamic processes including interfacial reactions, ion migration, charge transfer, and diffusion. Three categories of TI are defined to capture macroscopic parameter evolution, frequency-specific impedance responses, and microscopic dynamics with high precision. A dual-scenario experimental framework is designed, covering both factory-level sorting and wide-temperature calibration. SOC sampling intervals of 3 % and 5 % are compared, showing that high-resolution sampling reduces estimation error by 25.0 %. By combining feature–algorithm co-optimization with ensemble learning, temperature-adaptive SOC estimation is achieved. Among the three TI categories, feature TI delivers the best performance, with average errors of 3.53 % and 4.42 % under the two scenarios. In addition, nonlinear temperature interference on impedance features is identified, highlighting the robustness and broad applicability of the approach. This study breaks the limitations of voltage-based methods and offers an SOC estimation solution for LFP batteries that balances mechanistic insight with engineering feasibility.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138745"},"PeriodicalIF":9.4,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An innovative humidity Enhancement-RC-mapping model with tailored identification framework for building HVAC demand response applications 一个创新的湿度增强- rc映射模型，为建筑暖通空调需求响应应用量身定制识别框架

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-03 DOI: 10.1016/j.energy.2025.138772

Huilong Wang , Zhuoyue Tan , Jinhan Mo , Maomao Hu , Ying Ji , Cheng Fan

{"title":"An innovative humidity Enhancement-RC-mapping model with tailored identification framework for building HVAC demand response applications","authors":"Huilong Wang , Zhuoyue Tan , Jinhan Mo , Maomao Hu , Ying Ji , Cheng Fan","doi":"10.1016/j.energy.2025.138772","DOIUrl":"10.1016/j.energy.2025.138772","url":null,"abstract":"<div><div>The increasing adoption of renewable energy sources highlights the pressing demand for greater grid flexibility. Under such circumstances, grey-box modeling offers a practical approach for estimating building flexibility and facilitating demand response control. However, existing models still present limitations: First, conventional RC models are primarily designed to capture sensible heat dynamics, while failing to represent latent heat dynamics. In fact, latent heat changes can indirectly affect indoor temperature variation during demand response. Second, existing RC models primarily focus on buildings' thermal storage while overlooking air conditioning systems' thermal storage. To address these limitations, this study proposes a Humidity Enhancement (HE)-RC-Mapping model. This model introduces a formulation for the ratio of latent to sensible heat during demand response and considers the air conditioning systems' thermal storage, besides the buildings’ thermal storage. Dedicated to the proposed model, a tailored parameter identification framework incorporating a multi-condition stepwise identification strategy and a dual-objective function is introduced. Additionally, to ensure a more equitable and rigorous assessment of model performance under different temperature fluctuation ranges during demand response, this study proposes a new performance evaluation metric, the Relative RMSE Index (RRI). Experiments in a large public building demonstrate that the proposed model significantly outperforms the conventional RC model in predicting indoor temperature under cooling load reduction during demand response. Specifically, the RMSE of indoor temperature prediction is reduced from 0.737 °C to 0.118 °C, while the RRI is reduced from 173.24 % to 21.31 %.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138772"},"PeriodicalIF":9.4,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating the corporate performance in sustainable development of China's listed companies: a new series-parallel structure based on network DEA and BoD models 中国上市公司可持续发展中的公司绩效评价：基于网络DEA和BoD模型的串并联结构

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-03 DOI: 10.1016/j.energy.2025.138681

Ruchuan Zhang , Aijun Li , Xuenan Wu , Yao Wang

{"title":"Evaluating the corporate performance in sustainable development of China's listed companies: a new series-parallel structure based on network DEA and BoD models","authors":"Ruchuan Zhang , Aijun Li , Xuenan Wu , Yao Wang","doi":"10.1016/j.energy.2025.138681","DOIUrl":"10.1016/j.energy.2025.138681","url":null,"abstract":"<div><div>The sustainable finance's selective backing and the capital market's increasing attention on corporate sustainability highlight that evaluating listed companies' green performance is of crucial importance for investors. However, few studies have considered the aggregated performance of innovative, operational and environmental sub-systems. This study constructs a sustainability system of a series-parallel structure, and proposes a new methodological framework with several charming methodological advantages. Empirically, this study evaluates aggregated efficiency and technology inequality across China's 1065 listed companies from 2011 to 2021. The main findings are summarized as follows. First, the average efficiency of innovative sub-system (0.730) is lower than that of operational and environmental sub-systems, suggesting that listed companies still have much potential to enhance innovation capabilities. Second, according to results of direct and indirect network performance indexes, intermediate products are identified as important focus points for improving sustainability performance. Finally, the efficiency Gini coefficient reveals a widening gap in technical inequality among sample companies in the sustainability assessment system, with the growing disparity between the two sub-sample groups acting as a primary factor. This study provides policymakers with a robust approach for tracking sources of inefficiency, and then propose proactive strategies to enhance company sustainability.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138681"},"PeriodicalIF":9.4,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synergistic heat recovery–dissipation architecture for hydrogen turbofans: Integrated heat current modeling with multi-parameter thermodynamic analysis 氢涡轮风扇的协同热回收-散热结构：集成热流建模与多参数热力学分析

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-03 DOI: 10.1016/j.energy.2025.138735

Weitong Liu , Guoqiang Xu , Xiuting Gu , Yiang Liu , Jiayang Wang , Jingzhi Zhang , Yanchen Fu

{"title":"Synergistic heat recovery–dissipation architecture for hydrogen turbofans: Integrated heat current modeling with multi-parameter thermodynamic analysis","authors":"Weitong Liu , Guoqiang Xu , Xiuting Gu , Yiang Liu , Jiayang Wang , Jingzhi Zhang , Yanchen Fu","doi":"10.1016/j.energy.2025.138735","DOIUrl":"10.1016/j.energy.2025.138735","url":null,"abstract":"<div><div>Hydrogen-fueled aero engines offer a promising path toward decarbonizing aviation, but their adoption is hindered by the dual challenges of safely preheating cryogenic liquid hydrogen (LH<sub>2</sub>) and efficiently recovering onboard waste heat. Most studies focus on components or simplified models, overlooking phase-change effects and intermediate-cycle integration. Moreover, conventional mass-flow-based modeling introduces excessive intermediate variables, limiting efficiency and applicability in complex hydrogen turbofan systems. To address these gaps, this study proposes a novel synergistic heat recovery–dissipation architecture for hydrogen turbofan engines, incorporating four functional heat exchangers and a helium-based intermediate cycle. Besides, a novel energy-flow-oriented thermal modeling framework based on the heat current method is developed, coupled with a phase-change LH<sub>2</sub> preheating model. The model is validated against published data, yielding a temperature deviation below 23.15 K. Parametric analyses reveal that increasing turbine inlet temperature enhances heat transfer performance and thrust, while optimal values of bypass ratio (<em>B</em> = 2.4) and helium flow distribution (<em>ϕ</em> = 0.7) maximize thermal efficiency and preheated hydrogen temperature. Additionally, the helium mass flow rate and its distribution ratio provide effective yet saturable control over heat exchanger performance. These results demonstrate the viability of integrating intermediate-cycle systems into hydrogen turbofans and highlight the advantages of energy-flow-based modeling in reducing system complexity while capturing nonlinear thermal behavior. The proposed architecture and methodology provide new insights into the design of advanced thermal management systems and support the development of high-performance, zero-emission aviation propulsion technologies.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138735"},"PeriodicalIF":9.4,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Safe reinforcement learning-based energy management for fuel cell hybrid electric aircraft with longevity considerations 考虑寿命的燃料电池混合动力飞机安全强化学习能量管理

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-03 DOI: 10.1016/j.energy.2025.138782

Yajing Xiao , Jinning Zhang , Harold S. Ruiz , Ioannis Roumeliotis , Xin Zhang

{"title":"Safe reinforcement learning-based energy management for fuel cell hybrid electric aircraft with longevity considerations","authors":"Yajing Xiao , Jinning Zhang , Harold S. Ruiz , Ioannis Roumeliotis , Xin Zhang","doi":"10.1016/j.energy.2025.138782","DOIUrl":"10.1016/j.energy.2025.138782","url":null,"abstract":"<div><div>Fuel Cell Hybrid Electric Aircraft (FCHEA) represent a promising solution for decarbonizing short-to medium-range aviation. However, the hybrid-electric architecture introduces increased control complexity and poses challenges in ensuring component longevity and operational safety. Although reinforcement learning (RL)-based energy management strategies (EMS) have been explored in ground vehicle application, they often prioritize fuel efficiency while neglecting component degradation and safety-critical constraints, both of which are vital for the reliability of electric aviation. This study presents a Longevity-Conscious Safe Energy Management Strategy (LC-SEMS) to minimize operational and degradation-related costs over long-term use, while ensuring the satisfaction of multi-type constraint. The strategy is implemented within a multidisciplinary simulation framework that integrates propulsion, aerodynamics, hybrid powertrain, and flight dynamics models for mission-level evaluation. The EMS problem is formulated as a Constrained Markov Decision Process (CMDP) incorporating physical, cumulative, and instantaneous constraints. Instantaneous safety is enforced via an adaptive shielding mechanism that leverages a pretrained transition model to detect potential constraint violations and applies minimal corrective actions without interfering with policy learning. The proposed strategy is validated on a simulated FCHEA retrofitted from the NASA X-57 Maxwell, achieving fast convergence and strict constraint adherence across multi-mission scenarios. It achieves a 26.96 % reduction in depreciation cost compared to baseline RL-based EMS, with a minimal 4.21 % performance gap relative to the globally optimal Dynamic Programming (DP) benchmark, demonstrating its adaptability and robustness under uncertain and unseen mission scenarios.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138782"},"PeriodicalIF":9.4,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental study on the ejected flame behavior and near-field flame radiation characteristics from building compartment with double openings under crosswinds 侧风作用下双开口建筑隔室喷射火焰行为及近场火焰辐射特性实验研究

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-03 DOI: 10.1016/j.energy.2025.138773

Yipeng Zheng , Fei Tang , Xinyang Fan , Fei Ren , Xiang Fang , Longhua Hu

{"title":"Experimental study on the ejected flame behavior and near-field flame radiation characteristics from building compartment with double openings under crosswinds","authors":"Yipeng Zheng , Fei Tang , Xinyang Fan , Fei Ren , Xiang Fang , Longhua Hu","doi":"10.1016/j.energy.2025.138773","DOIUrl":"10.1016/j.energy.2025.138773","url":null,"abstract":"<div><div>With the acceleration of urbanization and the densification of high-rise building complexes, the integration of energy systems and the functional complexity of building spaces have led to the uncontrollable combustion within the energy building system. This study investigates the evolution of ejected flame behavior, flow field characteristics, and near-field flame radiation from a building compartment with double openings under crosswind conditions, combining numerical simulation and experimental methods. Experiments were performed using a reduced compartment with double openings of different separation distances. The results show the interaction between the ejected flame from a double-opening compartment, and it reveals three different stages with the variation of HRR and crosswind speed. During the most hazardous stage II, the interaction between the flames including the merging of the flames is analyzed, which can easily cause three-dimensional fires on the building facade, the upstream and downstream flame inclination angles were defined, and a quantitative model for these inclination angles was developed based on effective crosswind speed. Additionally, a quadrangular prismatic flame model was proposed based on the actual flame geometry. The study further analyzes the flame surface area, radiative fraction, and view factor to predict the near-field thermal radiation. In this work, the effect of crosswinds on the flame radiation distribution caused by ejected fires with two openings was studied and discussed, and the interaction mechanism between the two ejected flames from a compartment under crosswinds was revealed, thereby enhancing the understanding of combustion processes and near-field flame radiation characteristics in ejected flames from double openings along the facade.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138773"},"PeriodicalIF":9.4,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Climate-informed long-term forecasting of wind and photovoltaic power using a hybrid DWT–BES–CNN–LSTM model 利用DWT-BES-CNN-LSTM混合模型对风能和光伏发电的气候信息长期预测

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-03 DOI: 10.1016/j.energy.2025.138677

Xingchen Wei , Xinyu Wu , Kei Yoshimura , Chuntian Cheng , Hao Huang , Zhendong Ding , Yuhang Song

{"title":"Climate-informed long-term forecasting of wind and photovoltaic power using a hybrid DWT–BES–CNN–LSTM model","authors":"Xingchen Wei , Xinyu Wu , Kei Yoshimura , Chuntian Cheng , Hao Huang , Zhendong Ding , Yuhang Song","doi":"10.1016/j.energy.2025.138677","DOIUrl":"10.1016/j.energy.2025.138677","url":null,"abstract":"<div><div>Accurate long-term forecasting of wind and photovoltaic (PV) power is critical for climate-resilient energy system planning and grid operation. However, the inherent intermittency, nonlinearity, and climate sensitivity of renewable energy sources pose persistent challenges. To address this, we propose a hybrid deep learning framework that integrates Discrete Wavelet Transform (DWT), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and the Bald Eagle Search (BES) algorithm. The DWT enables multi-scale decomposition of power output time series, enhancing the model's ability to capture both high-frequency variability and long-term trends. The CNN–LSTM architecture jointly learns spatial–temporal patterns, while BES is employed to optimize key hyperparameters, improving model robustness and generalization. The framework is applied to monthly wind and PV power data from Guizhou Province, China (1953–2020), with large-scale climate indices and meteorological variables incorporated as exogenous drivers. Compared to the baseline LSTM model, the proposed DWT–BES–CNN–LSTM approach reduces RMSE by 40.3 %, 16.7 %, 30.2 %, and 16.7 % at stations W1, W2, P1, and P2, respectively, and achieves the highest R<sup>2</sup> scores across all benchmarks. These results demonstrate the framework's superior long-term predictive performance and its practical value in supporting low-carbon energy transition, grid reliability, and integrated planning under climate uncertainty.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138677"},"PeriodicalIF":9.4,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Empowering women to combat energy poverty in South Asia 赋予妇女权力以消除南亚的能源贫困

IF 9.4 1区工程技术

Energy Pub Date : 2025-10-03 DOI: 10.1016/j.energy.2025.138765

Shamal Chandra Karmaker , Kanchan Kumar Sen , Bipasha Singha , Andrew J. Chapman , Wasimul Bari , Shahadat Hosan , Bidyut Baran Saha

{"title":"Empowering women to combat energy poverty in South Asia","authors":"Shamal Chandra Karmaker , Kanchan Kumar Sen , Bipasha Singha , Andrew J. Chapman , Wasimul Bari , Shahadat Hosan , Bidyut Baran Saha","doi":"10.1016/j.energy.2025.138765","DOIUrl":"10.1016/j.energy.2025.138765","url":null,"abstract":"<div><div>Energy poverty remains a persistent challenge in South Asia, particularly among rural populations, however limited attention has been given to the role of women's empowerment in mitigating this issue. This study addresses this research gap by introducing a novel Multidimensional Women's Empowerment Index (MWEI) and investigating the relationship with multidimensional energy poverty across five South Asian countries. Utilizing nationally representative Demographic and Health Survey data from 2001 to 2018, we apply mixed-effects logistic regression and a two-stage least squares (2SLS) estimation to control for potential endogeneity and unobserved heterogeneity. The results revealed that higher levels of women's empowerment, defined through their participation in household decision-making, education, and employment, are significantly associated with reduced household energy poverty. Notably, countries such as India, Nepal, and Pakistan experienced energy poverty reductions of over 70 % in households with high MWEI scores. However, significant urban-rural disparities in energy poverty alleviation persist. This study contributes to the literature by empirically quantifying the causal link between women's empowerment and energy poverty reduction through a novel composite index and robust econometric techniques. The findings underscore the critical need for gender-inclusive energy and development policies, especially in rural areas, to effectively combat energy poverty and support the attainment of the Sustainable Development Goals.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"338 ","pages":"Article 138765"},"PeriodicalIF":9.4,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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