Sustainable Energy Grids & Networks最新文献_第4页

An alternating direction method of multipliers approach for the reconfiguration of radial electrical distribution systems 径向配电系统重构的乘法器交替方向法

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-24 DOI: 10.1016/j.segan.2025.101684

Yacine Mokhtari , Patrick Coirault , Emmanuel Moulay , Jérôme Le Ny , Didier Larraillet

{"title":"An alternating direction method of multipliers approach for the reconfiguration of radial electrical distribution systems","authors":"Yacine Mokhtari , Patrick Coirault , Emmanuel Moulay , Jérôme Le Ny , Didier Larraillet","doi":"10.1016/j.segan.2025.101684","DOIUrl":"10.1016/j.segan.2025.101684","url":null,"abstract":"<div><div>The electrical network reconfiguration problem aims to minimize losses in a distribution system by adjusting switches while ensuring the radiality (tree structure) of the network. Although this problem can be formulated as a mixed integer nonlinear program, solving the resulting optimization problem requires significant time and resources. A carefully selected initial solution, which can be identified by appropriate heuristics, reduces the search space, accelerates convergence, and ensures feasibility. This paper introduces two heuristic algorithms based on the Alternating Direction Method of Multipliers (ADMM) to address this problem. These heuristics break down the problem into smaller, more manageable subproblems that can be solved efficiently. Two algorithms are developed: one relies on natural variable substitution, and the other on a previously used relaxation technique. The challenge encountered in previous studies of incorporating radial constraints with ADMM is addressed by redefining the combinatorial subproblem in the projection step of ADMM as a minimum weight rooted arborescence problem, whose solutions are guaranteed to be radial. Convex optimization techniques can then handle the remaining subproblems. The performance of both heuristics is evaluated through numerical experiments on the 33-bus and 70-bus systems, as well as on a real-world electrical network.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101684"},"PeriodicalIF":4.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Two-layer eco-driving approach of connected hybrid electric vehicles by convex optimization via signalized intersections 基于凸优化的互联混合动力汽车信号交叉口双层生态驾驶方法

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-22 DOI: 10.1016/j.segan.2025.101687

Qiang Zhang , Jian Xiong , Ningyuan Guo , Zheng Chen , Yuanjian Zhang , Yonggang Liu , Jin Liu

{"title":"Two-layer eco-driving approach of connected hybrid electric vehicles by convex optimization via signalized intersections","authors":"Qiang Zhang , Jian Xiong , Ningyuan Guo , Zheng Chen , Yuanjian Zhang , Yonggang Liu , Jin Liu","doi":"10.1016/j.segan.2025.101687","DOIUrl":"10.1016/j.segan.2025.101687","url":null,"abstract":"<div><div>Developing a sophisticated energy-management-centered eco-driving method can significantly boost the driving economy of vehicles. However, current optimization methods for hybrid electric vehicles (HEV) in multi-traffic-light scenarios still have room to improve energy-saving optimality and computational efficiency. Hence, this paper proposes a two-layer convex approach for the eco-driving of connected HEVs at signalized intersections. In the upper layer, a convex motor-power model is built, and a position constraint within the green-light time window is decided using traffic light information and signal phase-and-timing data. Then, a convex velocity-planning problem to minimize motor energy consumption is formulated and efficiently solved. In the lower layer, the engine's optimal operating line and unified battery-power constraints are introduced, and a series of convexification steps are performed. This enables the establishment of a convex-optimization energy management problem for minimizing fuel consumption, facilitating fast solution. Results show that the proposed method can effectively manage multi-signal scenarios, allowing vehicles to pass through green lights and avoid red-light waits. Regarding motor energy and fuel consumption, it achieves near-optimal results, with a deviation of less than 2 % from the global optimum. The optimization takes only about 1 s (around 1/24000–1/6 to comparative methods’), indicating high computational efficiency.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101687"},"PeriodicalIF":4.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

New staggered time-of-use tariffs to mitigate the impact of electric vehicle charging demand on distribution networks 新的交错使用时间关税，以减轻电动汽车充电需求对配电网络的影响

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-22 DOI: 10.1016/j.segan.2025.101682

Yan Wu , Syed Mahfuzul Aziz , Mohammed H. Haque , Travis Kauschke

{"title":"New staggered time-of-use tariffs to mitigate the impact of electric vehicle charging demand on distribution networks","authors":"Yan Wu , Syed Mahfuzul Aziz , Mohammed H. Haque , Travis Kauschke","doi":"10.1016/j.segan.2025.101682","DOIUrl":"10.1016/j.segan.2025.101682","url":null,"abstract":"<div><div>The peak demand of the power grid determines the maximum capacity required for the network infrastructure. Even short-term high peaks can significantly increase the required capacity and hence increase the grid operational costs, wholesale market prices and retail prices. To reduce the peak demand, <em>time-of-use (TOU) tariffs</em> were introduced, encouraging customers to shift their electricity consumption to the <em>off-peak</em> periods. However, <em>conventional TOU tariffs</em> may exacerbate the grid peak demand due to increasing electric vehicle (EV) charging demand in the near future. To address the challenge, this paper proposes innovative <em>TOU tariffs</em> with staggered pricing segments and presents critical analysis based on a distribution network in Australia. The results indicate that the proposed <em>staggered TOU tariffs</em> offer significant advantages by spreading the EV charging demand over the <em>off-peak</em> periods. At 100 % EV penetration, if 50 % of the customers charge their EVs using a <em>staggered TOU tariff</em> then the peak-to-valley power difference in the daily average load profile can be reduced by 20.0 %, and the sum of standard deviation for transformer utilization can be decreased to less than 16.6 %. For 100 % <em>TOU</em> adoption rate, the proposed <em>staggered TOU tariffs</em> can meet the EV charging demand without causing overloading of the network transformers.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101682"},"PeriodicalIF":4.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Soft open points scheduling in unbalanced active distribution networks based on multi-agent graph reinforcement learning 基于多代理图强化学习的非平衡主动分配网络中的软开放点调度

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-22 DOI: 10.1016/j.segan.2025.101689

Liu Hong, Li Qizhe, Zhang Qiang, Xu Zhengyang, He Xingtang

{"title":"Soft open points scheduling in unbalanced active distribution networks based on multi-agent graph reinforcement learning","authors":"Liu Hong, Li Qizhe, Zhang Qiang, Xu Zhengyang, He Xingtang","doi":"10.1016/j.segan.2025.101689","DOIUrl":"10.1016/j.segan.2025.101689","url":null,"abstract":"<div><div>This paper proposes an innovative unbalanced ADN operation strategy utilizing multi-agent graph reinforcement learning (MAGRL), where SOPs are scheduled to mitigate the three-phase unbalance and minimize system loss. The SOP scheduling problem in unbalanced ADN is modeled as a multi-agent partially observable Markov decision process (POMDP). Then, a direct approach based Backward/Forward Sweep (BFS) power flow model is proposed in our framework to provide precise power flow results within a few iterations to the training environment. The graph convolution networks (GCNs) are embedded in the policy network to further improve the agent capability of learning and capturing spatial correlations and topological linkages among nodes in complex unbalanced ADN, hence promoting the effectiveness of action strategy for the agents. This model has been tested on modified three-phase unbalanced IEEE 123-node system and IEEE 8500-node system. The results illustrate the notable regulation capability of the proposed method for unbalanced ADN.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101689"},"PeriodicalIF":4.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Resilience-oriented distributed generation planning of distribution network under multiple extreme weather conditions 多种极端天气条件下面向弹性的配电网分布式发电规划

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-19 DOI: 10.1016/j.segan.2025.101675

Junji Zhou, Xiong Wu, Xuhan Zhang, Fengshuo Xiao, Yifan Zhang, Xiuli Wang

{"title":"Resilience-oriented distributed generation planning of distribution network under multiple extreme weather conditions","authors":"Junji Zhou, Xiong Wu, Xuhan Zhang, Fengshuo Xiao, Yifan Zhang, Xiuli Wang","doi":"10.1016/j.segan.2025.101675","DOIUrl":"10.1016/j.segan.2025.101675","url":null,"abstract":"<div><div>Planning resilient and elastic distribution networks has become an effective strategy for withstanding extreme weather events. However, conventional research often overlooks the impact of multiple extreme weather conditions and only considers planning for one specific type of extreme weather. This paper proposes a resilience-oriented distributed generation planning approach for distribution networks, which takes into account multiple extreme weather conditions. Firstly, a line fault probability model is established to capture the impact of typhoons, rainstorms, ice and snow weather. Secondly, a fault scenario generation and simplification method based on modified monte carlo simulation and <em>k</em>-means clustering is proposed to ensure the representativeness and computational efficiency of the selected scenarios. Additionally, a two-stage stochastic mixed integer programming model is introduced to enhance system resilience through distributed generation configuration and network topology reconstruction. The first stage focuses on determining the number, location, and size of distributed generation with economic objectives, while the second stage addresses the recovery method after an uncertain extreme event based on the distributed generation configuration obtained in the first stage. The proposed model is applied to modified IEEE 33-bus system and IEEE 123-bus system. Compared with the conventional method, the DG configuration results are consistent and the solution time is reduced by 70–80 %, achieving a balance between accuracy and efficiency. Furthermore, it effectively reduces load shedding by nearly 90 % by optimizing DG utilisation.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101675"},"PeriodicalIF":4.8,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Large-scale generation of geo-referenced power distribution grids from open data with load clustering 基于负载聚类的开放数据大规模地生成地理参考配电网

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-17 DOI: 10.1016/j.segan.2025.101678

Alfredo Oneto, Blazhe Gjorgiev, Filippo Tettamanti, Giovanni Sansavini

{"title":"Large-scale generation of geo-referenced power distribution grids from open data with load clustering","authors":"Alfredo Oneto, Blazhe Gjorgiev, Filippo Tettamanti, Giovanni Sansavini","doi":"10.1016/j.segan.2025.101678","DOIUrl":"10.1016/j.segan.2025.101678","url":null,"abstract":"<div><div>The availability of real power distribution grid data is often restricted due to privacy concerns and the lack of digitized representations, limiting spatially-resolved assessments of these systems. This inaccessibility has motivated the development of methods for generating synthetic grids. However, existing methods face challenges such as computational intractability for large-scale zones, restrictive topological assumptions, insufficient representation of electrical components, and inadequate consideration of geographical constraints. This work addresses the challenges by developing a model for the large-scale generation of synthetic geo-referenced low- and medium-voltage grids using publicly accessible data. It comprises a geographic load clustering algorithm, a procedure for generating graphical grid layouts, and a method for selecting operational topologies and line types. The model’s effectiveness and computational performance are demonstrated by generating synthetic low- and medium-voltage grids for Switzerland, with all generated grids made openly available.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101678"},"PeriodicalIF":4.8,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Behavioral analytics for optimized self-scheduling in sustainable local multi-carrier energy systems: A prospect theory approach 可持续局部多载波能源系统优化自调度的行为分析：前景理论方法

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-14 DOI: 10.1016/j.segan.2025.101679

Sobhan Dorahaki , S.M. Muyeen , Nima Amjady , Syed Shuibul Qarnain , Mohamed Benbouzid

{"title":"Behavioral analytics for optimized self-scheduling in sustainable local multi-carrier energy systems: A prospect theory approach","authors":"Sobhan Dorahaki , S.M. Muyeen , Nima Amjady , Syed Shuibul Qarnain , Mohamed Benbouzid","doi":"10.1016/j.segan.2025.101679","DOIUrl":"10.1016/j.segan.2025.101679","url":null,"abstract":"<div><div>The transition towards sustainable energy systems demands innovative solutions to overcome the challenges of integrating diverse energy carriers, fluctuating market dynamics, and operator decision-making complexities. The active involvement of local multi-carrier energy systems (LMCES) as virtual power plants in upstream energy markets is particularly hindered by the limitations of conventional optimization methods, which fail to capture the nuanced behavioral aspects of decision-making. This paper presents a novel prescriptive behavioral analytics framework for LMCES self-scheduling, integrating insights from prospect theory to address the operator’s behavioral tendencies, including loss aversion, subjective risk attitudes, and mental reference points. By embedding these behavioral considerations into a mixed integer linear programming (MILP) model, the proposed approach accounts for real-world decision-making complexities often overlooked in conventional economic theories based on rationality. Comparative analyses demonstrate that the proposed framework not only enhances the modeling of LMCES operators’ decision-making processes but also improves energy scheduling efficiency and supports sustainable energy transitions. The findings provide actionable insights for optimizing LMCES operations, advancing their role in achieving energy sustainability goals.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101679"},"PeriodicalIF":4.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A scalable energy internet approach for hop regulated peer-to-peer power trading with connectivity and preference constraints 一种可扩展的能源互联网方法，用于具有连通性和偏好约束的hop监管点对点电力交易

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-13 DOI: 10.1016/j.segan.2025.101668

Neethu Maya , Bala Kameshwar Poolla , Seshadhri Srinivasan , Alessandra Parisio , Narasimman Sundararajan , Suresh Sundaram

{"title":"A scalable energy internet approach for hop regulated peer-to-peer power trading with connectivity and preference constraints","authors":"Neethu Maya , Bala Kameshwar Poolla , Seshadhri Srinivasan , Alessandra Parisio , Narasimman Sundararajan , Suresh Sundaram","doi":"10.1016/j.segan.2025.101668","DOIUrl":"10.1016/j.segan.2025.101668","url":null,"abstract":"<div><div>Incentives to maximize Peer-to-Peer (P2P) power trading and the establishment of consumer-friendly distributed power markets are essential contributions to the decarbonization of the power sector. This paper presents a Connectivity and Preference Constrained Hop-Regulated Approach for Peer-to-Peer Trading (CPHPT) in sparsely connected communities with reduced infrastructure requirements. The CPHPT approach leverages graph theory to optimize P2P subscriber matching by regulating the maximum hops between the nodes in each routed path of P2P exchange. Simulations using real-world datasets in a 10-home community demonstrate that the CPHPT increases community participation by 29.49%, with P2P power exchanges comparable to full connectivity at reduced infrastructure requirements. When scaled to a 100-home community, the CPHPT approach achieves a marginal performance difference of 2.71% compared to full connectivity while lowering the connectivity infrastructure by 93.4%. The CPHPT approach has a mean runtime of 8.9 s for a 3-h window with 30-min intervals in a 100-home community, indicating its scalability and feasibility for real-time implementation.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101668"},"PeriodicalIF":4.8,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Extreme value statistics of peak residential electricity demand: Effect of aggregation and moving-average smoothing 居民用电高峰需求极值统计：聚合效应与移动平均平滑

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-13 DOI: 10.1016/j.segan.2025.101674

M.W. Jack , M.M. Bandi

{"title":"Extreme value statistics of peak residential electricity demand: Effect of aggregation and moving-average smoothing","authors":"M.W. Jack , M.M. Bandi","doi":"10.1016/j.segan.2025.101674","DOIUrl":"10.1016/j.segan.2025.101674","url":null,"abstract":"<div><div>Understanding the fluctuations in power demand is critical to the integration of variable renewable resources and the design of future electricity grids. We present an approach to determining the full statistical distribution of peak values of power demand based on extreme value statistics. We apply this method to characterizing the tails of the consumer demand distribution and exploring how peak electricity demand scales with aggregation over increasing numbers of consumers and moving-average smoothing at increasing timescales for two very different consumer groups. The results show evidence of fat tail distributions for some consumers. For both consumer groups, extreme values scale as an inverse power law with aggregation over increasing numbers of consumers and as a decaying exponential with the timescale of moving-average smoothing. Peak reduction by moving-average smoothing is much more sensitive to different sets of consumers than aggregation. As smoothing about a moving average is the primary effect of battery storage, this means that, in general, battery storage cannot play the same role as aggregation in reducing peak demand.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101674"},"PeriodicalIF":4.8,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the participation of energy storage systems in reserve markets using Decision Focused Learning 基于决策聚焦学习的储能系统在储备市场中的参与研究

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-03-13 DOI: 10.1016/j.segan.2025.101677

Ángel Paredes , Jean-François Toubeau , José A. Aguado , François Vallée

{"title":"On the participation of energy storage systems in reserve markets using Decision Focused Learning","authors":"Ángel Paredes , Jean-François Toubeau , José A. Aguado , François Vallée","doi":"10.1016/j.segan.2025.101677","DOIUrl":"10.1016/j.segan.2025.101677","url":null,"abstract":"<div><div>Battery Energy Storage Systems (BESSs) are particularly well-suited to deepen the decarbonisation of reserve markets, traditionally dominated by non-renewable generators. BESSs operators often rely on Predict-Then-Optimise (PTO) methods to participate in these markets, which focus on forecasting market conditions without directly considering the impact of subsequent decisions during training. Recently, learning models have evolved to incorporate decision outcomes during training, known as Decision Focused Learning (DFL) methodologies, which have the potential to increase market benefits. This paper introduces a DFL approach that integrates the decision-making process of BESSs when participating in reserve markets into the training of their predictive models. By expressing the optimisation problem as a primal–dual mapping using the Karush–Kuhn–Tucker (KKT) conditions, the proposed DFL method enables the regressor to learn from the BESS’s decisions, refining its predictions based on observed outcomes, improving decision accuracy and market performance. Results show that the proposed DFL approach outperforms traditional PTO methods, with up to a 9.5% increase in profits for a case study based on the Belgian secondary reserve market, highlighting its effectiveness in managing the complexities of dynamic market conditions.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101677"},"PeriodicalIF":4.8,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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