Energy Reports最新文献

{"title":"Optimizing smart grid flexibility with a hybrid MINLP framework for renewable integration in urban energy systems","authors":"Sameer Algburi ,&nbsp;Omer Al-Dulaimi ,&nbsp;Hassan Falah Fakhruldeen ,&nbsp;Shakhlo Isametdinova ,&nbsp;I.B. Sapaev ,&nbsp;Saiful Islam ,&nbsp;Quadri Noorulhasan Naveed ,&nbsp;Ayodele Lasisi ,&nbsp;Israa alhani ,&nbsp;Qusay Hassan ,&nbsp;Doaa H. Khalaf ,&nbsp;Michael Ssebunya ,&nbsp;Feryal Ibrahim Jabbar","doi":"10.1016/j.egyr.2025.06.009","DOIUrl":"10.1016/j.egyr.2025.06.009","url":null,"abstract":"<div><div>Urban grids face the challenge of expanding renewable deployment while curbing emissions and minimizing the capital burden of network reinforcements, all of which depend on effective flexibility integration. A hybrid optimization framework is introduced, combining Mixed-Integer Nonlinear Programming with a reformulated MILP structure to jointly size photovoltaic systems, battery storage, staged network upgrades, and the dynamic participation of electric vehicles as both load and distributed storage. Thousands of EV constraints are consolidated through a polytope-based approach, and reinforcement costs are captured using a piece-wise linear model tailored to feeder capacity increments. Application to the Tuwaiq Smart City network, covering 3780 households, employs one-minute resolution data for 2024 to benchmark five operational schemes: No Flexibility, Demand Response, Smart Charging, Vehicle-to-Grid, and Integrated Decentralised Energy Management (IDEM). Compared with the baseline, IDEM achieves a 43.8 % reduction in annualised system cost, 46 % decrease in peak imports, and capacity cuts of 75 % and 82 % for PV and storage respectively, alongside a 65 % drop in grid integration expenses. A Monte Carlo test of 150 runs confirms cost stability within ±6 %, validating the robustness of layered flexibility under stochastic solar and mobility profiles. Solving across a full-year span is achieved within minutes on standard hardware, confirming the framework’s practical value for strategic energy planning</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 508-523"},"PeriodicalIF":4.7,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330400","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":"Analyzing the impact of environmental technological regulations, energy security, and natural resources on energy intensity in the USA","authors":"Mucahit Aydin ,&nbsp;Esra Guney ,&nbsp;Tunahan Degirmenci ,&nbsp;Nazli Demirtas","doi":"10.1016/j.egyr.2025.06.013","DOIUrl":"10.1016/j.egyr.2025.06.013","url":null,"abstract":"<div><div>Energy intensity is a critical indicator of energy efficiency and sustainability. Energy efficiency may vary depending on the country's energy and environmental policies. If the energy security risk is too high, instead of long-term R&amp;D investments that will reduce the country's energy intensity, it may increase the use of fossil fuels to ensure energy stability in the short term. On the other hand, a relatively lower security risk may enable the economy to reduce energy intensity in the long term through R&amp;D investments. Although natural resources provide supply stability in the short term, they may increase security risks in the long term due to supply disruptions. Technological regulations can reduce energy intensity in the long term by making low-carbon energies, such as renewable and nuclear energy, more efficient. This study examines the impact of energy security risk, natural resources, technological regulation, and economic growth on energy intensity in the USA from 1990 to 2019. The study results show that energy security risk reduces energy intensity while natural resources and economic growth increase it. The USA, relying on economic development and abundant natural resources, lacks proactive innovation pursuits. The financial resources brought by economic growth must be directed to low-energy, low-carbon initiatives.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 500-507"},"PeriodicalIF":4.7,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330399","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":"The route towards green transformation: Mechanism of clean production enabled by enterprise digitization","authors":"Yurong Wang,&nbsp;Zeyang Chai ,&nbsp;Xinjie Zhu","doi":"10.1016/j.egyr.2025.06.025","DOIUrl":"10.1016/j.egyr.2025.06.025","url":null,"abstract":"<div><div>Enterprise green transformation (EGT) serves as a microeconomic driver of sustainable economic development. Digital technologies provide critical impetus for EGT by enabling intelligent and precise management of clean production processes. Investigating the impact of enterprise digitalization (ED) on EGT can enhance the effective use of digital technologies for promoting green development. In recent years, China’s level of digital development has significantly advanced, playing a crucial role in pursuing green development. This study explores the direct and indirect effects of ED on EGT from the mechanism of clean production, using data from publicly listed companies in China from 2009 to 2022. The results show that: First, ED significantly promotes EGT, and this causal relationship withstands a battery of robustness checks. Second, from the perspective of clean production mechanisms, ED can facilitate EGT through process optimization and end-of-pipe treatment, but source control mechanism fails to demonstrate a significant positive impact. Third, there is heterogeneity in the green transformation effects of ED, with more pronounced impacts in heavily polluting and state-owned enterprises, and in central and western region firms. Fourth, from a macro perspective, ED significantly enhances regional environmental quality and economic growth, suggesting it is a win-win path for ecological and economic development. These findings provide practical evidence for policymakers to develop ED incentive policies aligned with green development goals.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 386-400"},"PeriodicalIF":4.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322597","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":"Empowering energy sustainability: A cutting-edge ensemble network for precise power forecasting","authors":"Taimoor Khan,&nbsp;Chang Choi","doi":"10.1016/j.egyr.2025.06.011","DOIUrl":"10.1016/j.egyr.2025.06.011","url":null,"abstract":"<div><div>An appropriate forecasting model for electrical energy generation and consumption is considered a key demand of modern power management systems. Therefore, it has attracted considerable attention from researchers to develop efficient and precise energy forecasting methods. Energy forecasting for residential buildings and power generation sites is vital in energy future planning and convenient management. Mainstream energy forecasting methods including conventional Machine Learning (ML) and Deep Learning (DL) methods contain high levels of non-linearity between input and output which require more improvement with respect to robustness, forecasting performance, and generalization ability in terms of effective energy generation and consumption forecasting. To address these problems, this paper presents a hybrid forecasting model, integrating a modified Convolution Neural Network (CNN) and Gated Recurrent Units (GRU) followed by an attention mechanism. In this architecture, CNN is designed to extract spatial information in historical input data while GRU emphasizes temporal information sequentially. Additionally, the extracted features are then fed to the Soft Attention (SA) module, aiming to acquire the dominant patterns for final forecasting. To ensure a fair evaluation, this study conducted extensive experiments comparing the proposed CNNGRU-SA model with several competitive techniques over both power generation and consumption benchmarks, aiming to effectively determine and assess their performance. Overall, the experimental results justify that the proposed network achieved higher performance and outperformed across competitive networks over MSE, MAE, and RMSE. Hence, the proposed framework enhances the development of intelligent energy systems, supporting more effective and efficient power management within smart grid infrastructures.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 401-412"},"PeriodicalIF":4.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322501","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":"Optimal energy-saving operation strategy of 5G base station with communication caching","authors":"Chunguang Lu ,&nbsp;Jiaying Wang ,&nbsp;Junzhe Huang ,&nbsp;Tao Xiao ,&nbsp;Lei Yan","doi":"10.1016/j.egyr.2025.05.068","DOIUrl":"10.1016/j.egyr.2025.05.068","url":null,"abstract":"<div><div>To further explore the energy-saving potential of 5 G base stations, this paper proposes an energy-saving operation model for 5 G base stations that incorporates communication caching and linearization techniques. Firstly, in terms of energy equipment, the electrical component characteristics of the 5 G base station’s constituent units are modeled, including air conditioning loads, power supply systems, and energy storage systems. Secondly, with respect to communication equipment, the relationship between equipment power consumption and communication traffic is quantified, and a communication flow model incorporating caching technology is constructed. Finally, an energy-saving operation model is developed, which couples the energy equipment and communication equipment, and is formulated as a mixed-integer linear programming (MILP) problem. Case studies demonstrate that the proposed model effectively integrates the characteristics of electrical components and data flow, enhancing energy efficiency while satisfying user communication demands, thus contributing to the energy-saving goals of 5 G base stations.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 343-351"},"PeriodicalIF":4.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322503","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":"Multi-agent collaborative diffusion of CCUS in China’s thermal power industry under green financial policies: A stochastic evolutionary game model","authors":"Kai Guo ,&nbsp;Chengyuan Zhan ,&nbsp;Muqing Niu ,&nbsp;Zeyu Zheng ,&nbsp;Xiang Li","doi":"10.1016/j.egyr.2025.06.018","DOIUrl":"10.1016/j.egyr.2025.06.018","url":null,"abstract":"<div><div>As the largest carbon emitter, China's thermal power industry faces critical challenges in achieving dual carbon goals. This study constructs a tripartite stochastic evolutionary game model integrating government, financial institutions, and thermal power enterprises to analyze the collaborative diffusion of Carbon Capture, Utilization, and Storage (CCUS) technology under green financial policies. By incorporating Gaussian white noise to simulate real-world uncertainties and employing the Milstein method in MATLAB for numerical solutions, the key findings are as follows: (1) Gaussian white noise modeling accurately simulates CCUS diffusion dynamics across stakeholders, revealing uncertainty-driven interactions. (2) In China's tripartite decarbonization phase, thermal power enterprises show acute policy-market sensitivity, balanced by regulatory-financial institutional pillars. (3) Carbon trading has an asymmetric driving effect. A 20 % carbon quota cut shortens the enterprise decision-stabilization period by 20 % more than a 20 % price hike, yet it’s less effective than price regulation in stabilizing financial institutions’ strategies. (4) Green credit stability collapses below the 2.86 % rate threshold, while a 3 % rate optimizes system evolution. (5) Policy synergy has two optimal ranges. System evolution is best when technological investment subsidies hit 0.16 times the cost. Within the 3.15–4 times carbon-price penalty range, an optimal penalty multiplier can curb fluctuations, boost technology adoption, and promote strategy choices for all parties. This research provides theoretical and policy insights for CCUS diffusion in China, and based on the conclusions, suggests relevant policy adjustments to aid the low-carbon transition of China’s thermal power industry under its coal-dominated energy structure.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 352-370"},"PeriodicalIF":4.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322500","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":"Research hotspots and development trends of virtual power plant in the energy transition: A bibliometric analysis","authors":"Bin Zhong ,&nbsp;Junhao Yang ,&nbsp;Yong Chen ,&nbsp;Hui Fang","doi":"10.1016/j.egyr.2025.06.023","DOIUrl":"10.1016/j.egyr.2025.06.023","url":null,"abstract":"<div><div>As an emerging power system operation mode, virtual power plant has shown great potential in improving energy efficiency, enhancing grid stability, and promoting the integration of distributed energy resources. In order to gain a comprehensive insight into the research trends and development trends in the field of virtual power plant, a systematic bibliometric analysis was conducted on 1314 articles included in the WoS database from 2010 to 2024, covering research fields, published journals, core authors, major countries/regions and research institutions, and high-frequency keywords. The analysis shows that China’s research achievements in this field are abundant, accounting for more than 40 % of the published papers, among which North China Electric Power University is the research institution with the most published papers, and Zhongfu Tan and Liwei Ju from the university have conducted in-depth and extensive research. Energies and Applied Energy are the two journals with the largest number of publications. In addition, virtual power plant as energy fuels, power electronics technology and green manufacturing and other interdisciplinary research topics include not only mainstream research topics such as energy aggregation, demand response and power market, but also emerging technologies such as smart grids, electric vehicles and blockchain. At the same time, it also makes a detailed analysis of the national policy development, Research network expansion and excellent case reference of virtual power plant industry, which provides reference value for other countries.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 371-385"},"PeriodicalIF":4.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322502","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":"Control and optimization of grid-connected inverters for distributed generation using Ziegler–Nichols and Genetic Algorithm","authors":"Tiku Fidelis Etanya,&nbsp;Pierre Tsafack,&nbsp;Divine Khan Ngwashi","doi":"10.1016/j.egyr.2025.06.030","DOIUrl":"10.1016/j.egyr.2025.06.030","url":null,"abstract":"<div><div>The increasing integration of inverter-based distributed generation (DG) into modern power systems has heightened the need for advanced control strategies to maintain power quality and ensure efficient grid operation. This study proposes a control and optimization approach for grid-connected inverters for DG systems using Genetic Algorithms (GA), with performance benchmarked against the conventional Ziegler–Nichols (Z-N) method. A proportional–integral (PI) current control strategy is developed and formulated as a constrained multi-objective minimization problem, where controller gains are optimized using weighted objectives based on the Integral Time Absolute Error (ITAE), to enhance tracking accuracy, dynamic performance, and system stability across varying operating conditions. The system computes reference currents from active and reactive power generated by the DG’s, enhancing dynamic response and adaptability. It is validated under different power injection scenarios in single and dual-inverter DG configurations. The simulation results showed an improvement in the tracking efficiency of <span><math><mrow><mn>99.502</mn><mo>%</mo></mrow></math></span> using GA, surpassing <span><math><mrow><mn>90.135</mn><mo>%</mo></mrow></math></span> achieved with Z-N tuning. ITAE values for the GA-based direct quadrature axis PI controllers are <span><math><mn>0.205333</mn></math></span> and 0.151923, with steady-state errors of <span><math><mn>0.7</mn></math></span> and<span><math><mrow><mspace></mspace><mn>0.8</mn></mrow></math></span>, and a settling time of<span><math><mrow><mspace></mspace><mn>0.00526</mn><mi>s</mi></mrow></math></span>. In contrast, Z-N yielded higher ITAE values (1.76578 and<span><math><mrow><mspace></mspace><mn>1.65952</mn></mrow></math></span>) and a longer settling time of <span><math><mrow><mn>0.008005</mn><mi>s</mi></mrow></math></span>. FFT analysis shows negligible voltage distortion (0.00 %) and reduced current total harmonic distortion (0.22 % with GA, 1.98 % with Z-N), meeting IEEE 519–2014 and IEC 547 standards. The findings confirm that GA-based optimization significantly improves tracking, control accuracy, and power quality over conventional Z-N tuning, providing a robust solution for inverter control in grid-connected DG systems.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 413-431"},"PeriodicalIF":4.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330536","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":"Waste heat availability from hydrogen-based industries in district heating systems – A Swedish case study","authors":"Sofia Rosén ,&nbsp;Parvathy Sobha ,&nbsp;Cecilia Wallmark","doi":"10.1016/j.egyr.2025.06.028","DOIUrl":"10.1016/j.egyr.2025.06.028","url":null,"abstract":"<div><div>This study examines the changes in waste heat (WH) potential from existing and emerging hydrogen-based industries and their impact on district heating (DH) systems. Gällivare and Gothenburg, two Swedish municipalities with differing demographics, industries, energy needs, renewable potential, and climates, are assessed for their common role in the ongoing hydrogen-based industrial transition. Gällivare and Gothenburg are modelled using energy system optimization models, TIMES-City and the in-house City model respectively, and are assessed for 2050. In Gällivare, integrating WH from emerging hydrogen-based industries into DH could reduce electricity demand for heating by around 20 times, thereby freeing up power for the decarbonization of industry and transport. In the maximum WH scenario, DH’s share in heat supply reaches almost 100 %, reducing marginal heating costs by 22 % compared to the current level. In Gothenburg, recovered heat from electrolysis could meet up to 20 % of the annual heating demand. In general, Power-to-Heat technologies are preferred when WH availability is low. However, large-scale hydrogen production via electrolysis increases electricity grid congestion, leading to investments in combined heat and power plants to meet the demand for electricity locally.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 432-444"},"PeriodicalIF":4.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330401","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":"CCUS technology or renewable energy for India’s net zero carbon emission mission? Fuzzy analytical hierarchy process","authors":"Akanksha Singh ,&nbsp;Shweta Kumari ,&nbsp;Shiv Lal ,&nbsp;Magdalena Radulescu","doi":"10.1016/j.egyr.2025.06.015","DOIUrl":"10.1016/j.egyr.2025.06.015","url":null,"abstract":"<div><div>The trajectory of India’s energy system is a combination of technology and policy mix which extends to reliable, affordable and attainable energy sources. More than 60 % of electrical power is generated by coal in India as well as globally. The major air pollution take place due to the thermal power plants and the country needs to deploy carbon capture, utilization, and storage (CCUS) technology in thermal power plants that can help to decarbonize the economy. In present era, the CCUS is a cutting-edge technology for the power plants and Industries. The paper is validating the use of CCUS technology as a better option for India in the present scenario. The Fuzzy Analytical Hierarchy Process (FAHP) multi-criteria method is used to compare the potential of CCUS and renewable energy. The value of CCUS is evaluated by 0.981 and the value of Renewables (REW) is 0.609 in India. Presently the study suggests that CCUS has an advantage over (Renewables) REW in comparison to time taken for CO₂ reduction and present energy mix is in favorable for CCUS whereas REW has a cost advantage over CCUS. The Business As Usual (BAU) estimation is also forecasted the future energy demand and CO₂ reduction till 2050.</div></div>","PeriodicalId":11798,"journal":{"name":"Energy Reports","volume":"14 ","pages":"Pages 332-342"},"PeriodicalIF":4.7,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313164","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}