Energy Reports最新文献

{"title":"Ultra-short-term wind power forecasting: A hybrid parallel architecture integrating informer and SENet-enhanced temporal convolutional networks","authors":"Haoyang Xue,&nbsp;Fei Yu,&nbsp;Jiaming Qi,&nbsp;Xiaoqian Yue,&nbsp;Xinrui Pei","doi":"10.1016/j.egyr.2025.07.005","DOIUrl":"10.1016/j.egyr.2025.07.005","url":null,"abstract":"<div><div>In recent years, the increasing share of wind energy in power grids has made wind power forecasting crucial for grid stability and efficiency. Advanced technologies such as deep learning have improved forecasting, particularly in addressing the volatility and complexity of wind power data. However, existing studies often lack effective model integration and optimal hyperparameter tuning. Many complex algorithms fail to achieve synergy, and latent information in wind power data remains underexplored, limiting further accuracy improvements. Therefore, efficiently integrating deep learning methods and fully mining data features are key challenges for advancing ultra-short-term wind power forecasting. This paper proposes an ultra-short-term wind power forecasting model based on the parallel fusion of Informer and TCN-SENet architectures. The model fully leverages the efficiency of Informer in long-sequence modeling and the sensitivity of TCN-SENet to local temporal features. Through feature engineering and a sliding window mechanism, the model achieves high-precision forecasting with multivariate inputs and univariate outputs. This paper conducts comparative experiments using real-world wind farm datasets against Transformer-encoder, Informer, and their improved variants. The results demonstrate that this paper’s model consistently outperforms the benchmark models across all performance metrics, exhibiting superior generalization ability and robustness. Furthermore, this paper’s model shows clear advantages in capturing both the trend and fine-grained variations of wind power output. This paper provides an effective new approach for ultra-short-term, high-precision wind power forecasting, and offers theoretical and methodological support for smart grid scheduling and renewable energy integration.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1194-1206"},"PeriodicalIF":4.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Whale optimization-based clustering for buildings’ energy consumption profiles","authors":"Viorica Rozina Chifu,&nbsp;Tudor Cioara,&nbsp;Ionela Danci,&nbsp;Cristina Bianca Pop,&nbsp;Ionut Anghel","doi":"10.1016/j.egyr.2025.07.034","DOIUrl":"10.1016/j.egyr.2025.07.034","url":null,"abstract":"<div><div>The smart grids require advanced building demand-side management solutions to balance variable renewable production. Energy consumption profile segmentation can increase the efficiency of the processes, enabling grid operators to provide more personalized requests to different customer needs and behaviors increasing engagement and participant satisfaction. However, the complexity of clustering energy profiles is amplified by the diversity of consumer behavior and the need to adapt segmentation over time as consumption patterns evolve. Establishing the number of consumer energy profile clusters in advance is challenging, as most clustering algorithms are sensitive to initial parameter settings, which can affect their performance. In this paper, we propose a new clustering method based on the Whale Optimization Algorithm (WOA), which addresses the problem of dynamicity and variability of energy data. The whale individual is defined as a set of active centroids described by a compressive set of features extracted based on peak and valley periods focused on magnitude, variation, and efficiency. To promote compact and well-separated clusters of energy profiles the Calinski-Harabasz index was used as a fitness function. Population initialization is performed using K-Means+ + algorithm which ensures a diversified initial distribution of solutions in the solution space. The evolution of solutions is ensured through the mechanisms of the WOA algorithm, which allow the gradual updating of candidate solutions to accelerate convergence and produces high-quality solutions. The efficiency of the method was evaluated on a real dataset of daily energy consumption of buildings on a university campus. The experimental results show that the WOA method outperforms the selected state-of-the-art methods for comparison. WOA obtained the lowest Davies–Bouldin index (0.527), the highest Silhouette score (0.484) and the lowest Ball–Hall coefficient (1.851), indicating superior segmentation in terms of both internal cohesion and inter-cluster separability.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1207-1221"},"PeriodicalIF":4.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A decision support framework for electric demand planning in distribution systems during extreme minimum temperatures","authors":"Anyama Tettey ,&nbsp;Hieu Pham ,&nbsp;Howard Chen ,&nbsp;Dongsheng Wu ,&nbsp;Ana Wooley","doi":"10.1016/j.egyr.2025.06.020","DOIUrl":"10.1016/j.egyr.2025.06.020","url":null,"abstract":"<div><div>Records of underestimated electric demands during winter storms in the southeastern United States (US), like Uri and Elliot, contributed to national disasters, outages, and loss of lives and property during those temperatures when electricity was most needed. A regional utility organization in the Southeastern US reported that demand-related issues caused 97% of distribution system outages during Winter Storm Elliot in December 2022. If decision-makers and operators possessed timely knowledge of winter-peaking distribution networks in advance, they could have applied proactive mitigation measures to avoid several outages. Existing research emphasizes electric demand forecasts at system levels like cities and overall utilities. However, there is a notable gap in analytical frameworks that apply machine learning techniques for predictive modeling and proactive planning within distribution systems of US power grids targeted at minimum temperature planning. We propose a novel analytical and empirically validated decision-making framework that utilizes machine learning and statistical techniques for effective demand modeling and planning within distribution systems of applicable power grids.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1137-1148"},"PeriodicalIF":4.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accurate state-of-charge estimation of LiFePO4 battery: An adaptive extended kalman filter approach using particle swarm optimization","authors":"Xihong Lu ,&nbsp;Mingyang Chen ,&nbsp;Yong Tian","doi":"10.1016/j.egyr.2025.07.023","DOIUrl":"10.1016/j.egyr.2025.07.023","url":null,"abstract":"<div><div>Ensuring the safety and reliability of LiFePO₄ battery relies heavily on accurate state of charge (SOC) estimation. The Extended Kalman Filter (EKF) algorithm is widely used for SOC estimation, but this method struggles to distinguish subtle open circuit voltage (OCV) variations and often misinterprets them as noise. This poses a challenge to the methodology for estimating SOC based on OCV. In this paper, an innovative method is presented to overcome this issue and enhance SOC estimation accuracy during the OCV plateau period. This method introduces an adaptive gain in the EKF, which is specifically designed for the OCV plateau period. To optimize the parameters of the adaptive gain function and improve the convergence performance of the estimator, Particle Swarm Optimization (PSO) is employed. By adapting the Kalman gain dynamically with this adaptive gain, the EKF effectively rebalances the confidence level between prior estimation and measurement, which can reduce the impact of OCV noise on SOC estimation and improve accuracy significantly. Extensive simulation experiments validate the practicality and effectiveness of this method and demonstrate its ability to enhance SOC estimation accuracy for LiFePO₄ battery during the OCV plateau period. Compared with the traditional EKF, the maximum error of this method does not exceed 2 %, and the average MAE is reduced by 27.64 % and the average MSE is reduced by 39.24 %.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1169-1178"},"PeriodicalIF":4.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simplified sensorless predictive control of grid-side converter in wind energy conversion systems under distorted grid conditions","authors":"Adel Rahoui ,&nbsp;Koussaila Mesbah ,&nbsp;Boussad Boukais ,&nbsp;Noumidia Amoura ,&nbsp;Abdelhakim Saim ,&nbsp;Azeddine Houari","doi":"10.1016/j.egyr.2025.06.054","DOIUrl":"10.1016/j.egyr.2025.06.054","url":null,"abstract":"<div><div>This paper proposes a new direct power control (DPC) strategy without voltage sensors for grid-connected pulse width modulation converters in wind energy conversion systems. This method relies on model predictive DPC (MPDPC) combined with virtual flux (VF) estimation. A novel VF estimator, based on an adaptive linear neuron (ADALINE) configured as a quadrature signal generator, is designed to eliminate the need for grid voltage sensors. In parallel, a simplified MPDPC approach is introduced, optimizing the selection process of the optimal control vector by reducing the number of equations involved. This simplification lowers computational demands while maintaining high control performance. The combination of the simplified MPDPC and the proposed VF estimator results in a sensorless voltage control strategy, referred to as VF-SMPDPC. The proposed strategy is validated through real-time simulations using the OPAL-RT system. A comprehensive comparative analysis demonstrates the superior performance of the ADALINE-based estimator over other VF estimation methods. Furthermore, the VF-SMPDPC strategy significantly outperforms conventional MPDPC, particularly under distorted grid conditions, proving its effectiveness and robustness in practical applications.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1156-1168"},"PeriodicalIF":4.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategic investigation of EOR by surfactant-assisted CO₂-WAG: A pathway toward low-carbon oil production","authors":"Xiongzhi Liu ,&nbsp;Yongqiang Qu ,&nbsp;Lifei Dong ,&nbsp;Guoliang Yan ,&nbsp;Qifei Fang ,&nbsp;Hao Kang","doi":"10.1016/j.egyr.2025.07.019","DOIUrl":"10.1016/j.egyr.2025.07.019","url":null,"abstract":"<div><div>The target reservoir contains a high proportion of heavy components in the crude oil, resulting in a high minimum miscibility pressure (MMP) between CO₂ and the crude. Additionally, conventional CO₂-WAG flooding is prone to gas channeling, leading to premature gas breakthrough at production wells. This study investigates the synergistic potential of surfactant-assisted CO₂ water-alternating-gas (SA-CO₂-WAG) technology to enhance oil recovery while concurrently addressing low-carbon oil production. Through systematic core flooding experiments under actual reservoir conditions (93°C, 22 MPa), the research evaluates the impact of surfactant concentration (0.1–0.5 wt%) and injection rate (0.1–0.4 mL/min) on recovery efficiency. Results demonstrate that SA-CO₂-WAG significantly outperforms conventional CO₂-WAG, achieving an incremental recovery of 24 % compared to 16.2 % for CO₂-WAG, attributed to interfacial tension reduction, wettability alteration, and foam stabilization. Optimal performance was observed at 0.3 wt% surfactant concentration and 0.2 mL/min injection rate, beyond which diminishing returns occurred due to micellization, pore-throat blockage, and adsorption saturation. The study further explores policy frameworks to accelerate SA-CO₂-WAG deployment, emphasizing standardized parameter guidelines, carbon credit incentives, and cross-sectoral infrastructure integration. These findings highlight SA-CO₂-WAG as a dual-purpose solution for low-carbon oil production and carbon sequestration, aligning with global energy transition goals.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1149-1155"},"PeriodicalIF":4.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of waste heat sources for district heating","authors":"Olamide Opadokun ,&nbsp;Yong X. Tao ,&nbsp;Julian Lamb","doi":"10.1016/j.egyr.2025.07.015","DOIUrl":"10.1016/j.egyr.2025.07.015","url":null,"abstract":"<div><div>As the world’s energy needs rise, carbon emissions and climate change become a bigger concern. Therefore, there is a growing need for cleaner energy sources as well as higher levels of energy efficiency. Building energy is of great interest to researchers and policymakers, as it accounts for about a third of global energy consumption, and this is projected to rise as more people gain access to higher incomes and improved amenities. For over a century, district energy systems have proved to be an efficient means of providing thermal energy to buildings, and developments in district heating have enabled the use of various heat sources, including low-temperature sources, such as waste heat. Waste heat is a viable and technically mature source of building energy, as proven by many operational cases, but there seem to be only a few sources of waste heat utilized in practice or explored in literature. Additionally, many research studies focus on only one source of waste heat for district heating and, to the knowledge of the authors, there is currently no existing review paper on the various sources of waste heat utilized in district heating. Therefore, the goal of this paper is to examine various sources of waste heat that are utilized in real operational district heating cases or discussed in research studies. Additionally, the paper discusses the various performance metrics utilized for quantifying waste heat potential in existing literature, and rounds off with recommended future study.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1051-1070"},"PeriodicalIF":4.7,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active DC to DC converter based battery charge balancing systems from renewable energy by using electric vehicle","authors":"Tawfikur Rahman ,&nbsp;Nibedita Deb ,&nbsp;Samia Larguech ,&nbsp;Md. Moniruzzaman ,&nbsp;Noorlindawaty Md Jizat ,&nbsp;Sultan S. Alharbi ,&nbsp;Samir Salem Al-Bawri","doi":"10.1016/j.egyr.2025.07.026","DOIUrl":"10.1016/j.egyr.2025.07.026","url":null,"abstract":"<div><div>The increasing integration of electric vehicles (EVs) with smart grids demands efficient and intelligent battery management systems. This study presents a novel bidirectional DC-DC converter-based active balancing topology that supports dual operational modes for energy exchange between microgrids and EVs. The system incorporates a Combined Discharge and Balancing Circuit (CDBC) and a modular pulse-width modulation (PWM) control strategy to enable dynamic charge redistribution and support both active and reactive balancing. The proposed topology enhances system flexibility, reduces energy losses, and allows real-time voltage and current equalization across multiple battery cells. Numerical simulations conducted in MATLAB/Simulink demonstrate the superiority of the method compared to traditional passive and active balancing approaches. On average, the system achieves higher balancing efficiency and available capacity with reduced balancing time, even under varying cell conditions. This work contributes a scalable and efficient solution for next-generation battery management systems, offering practical relevance for applications in electric mobility, distributed energy storage, and grid-interactive infrastructures. The simulation framework also establishes a strong foundation for future experimental validation and hardware implementation.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1114-1136"},"PeriodicalIF":4.7,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing cost-efficiency and sustainability in offshore hybrid renewable energy systems: A case study of Palau River","authors":"Musa Terkes ,&nbsp;Muhammad Rızqi Asy Syarif ,&nbsp;Alpaslan Demirci ,&nbsp;Zafer Ozturk ,&nbsp;Erdin Gokalp ,&nbsp;Umit Cali","doi":"10.1016/j.egyr.2025.06.053","DOIUrl":"10.1016/j.egyr.2025.06.053","url":null,"abstract":"<div><div>Increasing environmental concerns and regulations on carbon emissions necessitate the development of economically viable and sustainable renewable energy systems. In this context, comprehensively evaluating solar PV-based hybrid energy systems under carbon tax (CT) scenarios is critically important. This study comparatively analyzes the cost-effectiveness, sustainability, and economic impacts of carbon taxation on both grid-connected and off-grid system configurations. Specifically, the effects of a CT on the costs of grid-connected system architectures are examined in detail, and cost reduction rates at various CTs are presented. By comparing different configurations in terms of technical performance and environmental benefits, optimal sizing strategies are determined to balance cost and carbon emissions. The results indicate that CT implementation provides a cost advantage in grid-connected systems, leading to a reduction in total system costs by approximately 15–22 %. Moreover, hybrid systems demonstrate significant improvements in environmental sustainability. These findings clearly highlight a critical role of CT policies in renewable energy integration and the economic and environmental benefits of hybrid energy systems.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1095-1113"},"PeriodicalIF":4.7,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical analysis of the effect of inner pipe thermal conductivity on heat transfer in deep borehole heat exchangers","authors":"Chunqiang Shen ,&nbsp;Chao Jiang ,&nbsp;Chao Li ,&nbsp;Juan Li ,&nbsp;Jiachen Wang ,&nbsp;Liguo Zhao","doi":"10.1016/j.egyr.2025.07.030","DOIUrl":"10.1016/j.egyr.2025.07.030","url":null,"abstract":"<div><div>Geothermal energy, recognized as a clean and sustainable solution, has become crucial to global energy transformation. This study focuses on a coaxial-type deep borehole heat exchanger geothermal utilization system in Xi’an to establish a comprehensive numerical model to investigate the effects of varying thermal conductivity and insulation depths of the inner pipe on the heat transfer performance of a deep-buried pipe. The results showed that the heat transfer rate of the buried pipe under different water temperature conditions is approximately 16 % higher with an insulated steel inner pipe than with a PE pipe. When the depth of the insulated steel pipe reaches 600 m, despite the insulation depth increasing by only 24.00 %, the heat loss rate of the buried pipe is significantly reduced to 43.07 %, which shows that an insulated inner pipe to a specific depth can effectively enhance the heat transfer of the buried pipe. This study presents a novel approach to enhance heat transfer in coaxial-type deep-buried pipes by focusing on inner pipe material selection and segmented thermal insulation. The findings offer valuable guidance on the design of deep-buried pipe heat transfer systems.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 1071-1079"},"PeriodicalIF":4.7,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678739","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}