Sustainable Energy Grids & Networks最新文献_第2页

A multivariate prediction framework for flood-induced substation damage based on generative adversarial network and MPformer-based two-stage model 基于生成对抗网络和基于mpform的两阶段模型的变电站洪水损伤多元预测框架

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-16 DOI: 10.1016/j.segan.2025.101740

Yu Shi , Ying Shi , Degui Yao , Ming Lu , Yun Liang , Wei Huang

{"title":"A multivariate prediction framework for flood-induced substation damage based on generative adversarial network and MPformer-based two-stage model","authors":"Yu Shi , Ying Shi , Degui Yao , Ming Lu , Yun Liang , Wei Huang","doi":"10.1016/j.segan.2025.101740","DOIUrl":"10.1016/j.segan.2025.101740","url":null,"abstract":"<div><div>Frequent extreme rainstorms have significantly increased the flooding risk, threatening the security and stability of electrical substations. The process of flood-induced substation damage is complex and nonlinear, challenging traditional predictive methods. Therefore, a novel predictive framework is proposed for flood-induced substation damage. This framework uses a generative adversarial network (GAN)-based model to capture complex data relationships and generate realistic samples, which mitigates training data imbalance. A multivariate predictive Transformer network (MPformer), integrating three improved modules: time embedding, multi-factor fusion encoding, and attention-based encoder, is proposed to capture temporal dependencies and complex interactions between influencing factors and flood-induced damage. Based on MPformer and sensitive cost learning, a two-stage integrated model is designed to reduce the problem of sample imbalance further and realize the simultaneous prediction of the substation damage probability, severity, and time. The experimental results show that the GAN-based method is superior to the traditional method in terms of sample balancing, and the MPformer-based two-stage model outperforms the mainstream model, with a 12.30 % average increase in F1 score for probability prediction and reductions of 38.56 % and 45.31 % in RMSE for severity and time predictions, respectively. A case study shows that the proposed method can offer reliable pre-disaster prediction.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101740"},"PeriodicalIF":4.8,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105619","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

Multi-objective smart charging scheduling scheme for EV integration and energy loss minimization in active distribution networks using mixed integer programming 基于混合整数规划的有源配电网电动汽车集成和能量损失最小化的多目标智能充电调度方案

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-14 DOI: 10.1016/j.segan.2025.101743

Subhadarshini Panda, Sanjib Ganguly

{"title":"Multi-objective smart charging scheduling scheme for EV integration and energy loss minimization in active distribution networks using mixed integer programming","authors":"Subhadarshini Panda, Sanjib Ganguly","doi":"10.1016/j.segan.2025.101743","DOIUrl":"10.1016/j.segan.2025.101743","url":null,"abstract":"<div><div>Efficient scheduling of electric vehicles (EVs) within power distribution networks (PDNs) is crucial due to the conflicting interests of various stakeholders, such as EV owners, who seek cost savings, and distribution network operators (DNOs), who focus on minimizing peak demand and reducing losses. This issue becomes even more pronounced with vehicle-to-grid (V2G) operations. This paper proposes a multi-objective EV scheduling model to determine the optimal trade-off between the economic interests of EV owners and the technical needs of the grid, thereby offering benefits to both stakeholders. The proposed model minimizes the total charging cost of EV owners and flattens the load curve in the EV-integrated PDN simultaneously. This is achieved by optimally utilizing both the grid-to-vehicle (G2V) and V2G capabilities of EVs while also considering battery health. A weighted sum method is used to find a set of non-dominated solutions to the multi-objective EV scheduling problem. Additionally, to further enhance the network efficiency and complement the multi-objective EV scheduling, the model incorporates distribution network reconfiguration (DNR) that is carried out at each hour of the day. The efficacy of the proposed model is validated by implementing it on a modified 33-node and IEEE 123-node test networks.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101743"},"PeriodicalIF":4.8,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070584","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

Power coordinated strategy of vehicle-to-microgrid integrated hybrid AC/DC microgrids considering electric vehicles as flexible energy storage 考虑电动汽车柔性储能的车-微网一体化交/直流混合微网功率协调策略

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-14 DOI: 10.1016/j.segan.2025.101737

Hao Wang , Jiawei Yan , Boyang Kang

{"title":"Power coordinated strategy of vehicle-to-microgrid integrated hybrid AC/DC microgrids considering electric vehicles as flexible energy storage","authors":"Hao Wang , Jiawei Yan , Boyang Kang","doi":"10.1016/j.segan.2025.101737","DOIUrl":"10.1016/j.segan.2025.101737","url":null,"abstract":"<div><div>Increasing adoption of electric vehicles (EVs) entrance to hybrid ac/dc microgrids (HMGs) would provide flexible energy storage sources (FESSs) to perform vehicle-to-microgrid (V2MG) operation. However, especially in islanded mode, the state of charge (SOC) of traditional energy storage unit (ESU) approaching the critical value of charge/discharge would inevitably lead to unreliable power supply. To solve this problem, a power coordinated strategy of V2MG integrated HMGs considering EVs as FESSs is proposed in this paper. First, a joint energy storage sources (JESSs) dynamic grouping method is presented for traditional ESU and scaled electric vehicle groups (EVGs) within HMGs containing multiple subgrids, which divides ESU and EVGs into panels and sets at the same time scale. Then, the operation modes and conditions of HMGs are classified according to the power surplus/deficient state of each subgrid. Further, this paper designs response priority based on real-time grouping of JESSs to balance the SOC of ESU and formulates power coordination control strategies for abnormal SOC of ESU and subgrid power overlimit, among which the FESSs provide auxiliary service for system power regulation. Finally, the results of the simulation analysis show that the proposed strategy can achieve coordinated regulation of traditional ESU and EV as FESSs in islanded microgrids, reducing the system's dependence on traditional ESU and improving the power supply reliability of microgrid systems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101737"},"PeriodicalIF":4.8,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084534","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

Load peak-valley shape clustering and drift analysis for improving temporal pattern representation 负载峰谷形状聚类和漂移分析改进时间模式表示

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-14 DOI: 10.1016/j.segan.2025.101734

Yiwei Ma , Yimeng Shen , Xianlun Tang , Dong Yan

{"title":"Load peak-valley shape clustering and drift analysis for improving temporal pattern representation","authors":"Yiwei Ma , Yimeng Shen , Xianlun Tang , Dong Yan","doi":"10.1016/j.segan.2025.101734","DOIUrl":"10.1016/j.segan.2025.101734","url":null,"abstract":"<div><div>Load shape pattern clustering is an important foundation for developing appropriate tariff design and load management to achieve more economical and reliable benefits. However, the existing load shape pattern clustering methods mainly focus on the whole load shape and various clustering algorithms, which do not consider the peak-valley shape features and distribution drift issue of the load shapes. Therefore, peak-valley shape pattern clustering and drift measurement of daily load shapes are proposed to solve this problem. To accurately reveal the peak-valley electricity consumption behaviors, load peak-valley shape models and a hybrid distance measurement are proposed to obtain more representative temporal patterns that have more compact peak-valley shape distributions. Moreover, two measurement models for power drift and time drift are proposed to analyze the significant drift problem between daily load peak-valley shape patterns. The results showed that the proposed method outperformed other methods, as it not only achieved the best clustering effectiveness scores, such as DBI, WAS, CHI, SC, and DI scores of 0.5537, 0.2633, 502.3634, 0.8872, and 1.4730, respectively, but also accurately obtained the time drift values between different modes, such as the maximum backward shift of the two peak times by 90 and 150 minutes, and the maximum backward shift of the valley time by 45 and 60 minutes, respectively.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101734"},"PeriodicalIF":4.8,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070581","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

Predicting faults in power distribution grids during heatwaves: A comparative study of machine learning models applied to Milan distribution network 热浪期间配电网故障预测：应用于米兰配电网的机器学习模型的比较研究

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-13 DOI: 10.1016/j.segan.2025.101741

Morteza Aghahadi , Alessandro Bosisio , Andrea Pegoiani , Samuele Forciniti , Marco Merlo , Alberto Berizzi

{"title":"Predicting faults in power distribution grids during heatwaves: A comparative study of machine learning models applied to Milan distribution network","authors":"Morteza Aghahadi , Alessandro Bosisio , Andrea Pegoiani , Samuele Forciniti , Marco Merlo , Alberto Berizzi","doi":"10.1016/j.segan.2025.101741","DOIUrl":"10.1016/j.segan.2025.101741","url":null,"abstract":"<div><div>The increasing frequency and severity of extreme weather events, such as heatwaves in Milan, intensified by climate change, pose significant challenges to the reliability and resilience of electrical power distribution systems. Traditional deterministic planning methods are becoming inadequate as these events grow more unpredictable. This study introduces a novel machine learning methodology to enhance grid resilience during heatwaves, focusing on fault prediction and heatwave forecasting. Three complementary approaches were systematically evaluated: Ridge Regression with Recursive Feature Elimination and Cross-Validation, Random Forest Regression, and Second-order Polynomial Poisson Regression with Recursive Feature Elimination and Cross-Validation. Through innovative feature engineering incorporating soil temperature, humidity gradients, and dynamic load demand patterns, predictive accuracy was significantly improved over conventional methods. Rigorous cross-validation with statistical validation demonstrated model stability across varying conditions, with the Second-order Polynomial Poisson model achieving a mean absolute error of 0.15 in predicting fault occurrences. To address the observed heteroscedasticity during high-fault periods, adaptive prediction intervals were developed, providing operators with crucial uncertainty quantification when it matters most. When translated to operational reality, these models enable Distribution System Operators to implement proactive fault management strategies, potentially reducing outage response times by an estimated 15–20 % during extreme weather events. This research bridges the critical gap between climate science and power system engineering, offering data-driven decision support for the increasingly volatile operational environment facing urban distribution networks.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101741"},"PeriodicalIF":4.8,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070583","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

A novel approach to optimize and allocate battery energy storage system in distributed grid considering impact of demand response program 考虑需求响应方案影响的分布式电网电池储能系统优化分配新方法

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-13 DOI: 10.1016/j.segan.2025.101738

Anh Nguyen-Tuan , Bach Ta-Duy , Tuyen Nguyen-Duc , Goro Fujita

{"title":"A novel approach to optimize and allocate battery energy storage system in distributed grid considering impact of demand response program","authors":"Anh Nguyen-Tuan , Bach Ta-Duy , Tuyen Nguyen-Duc , Goro Fujita","doi":"10.1016/j.segan.2025.101738","DOIUrl":"10.1016/j.segan.2025.101738","url":null,"abstract":"<div><div>Maintaining grid voltage within operational limits poses a significant challenge in distribution power systems, particularly with the increasing integration of Renewable Energy Sources (RES). This paper introduces an innovative management strategy for Battery Energy Storage System (BESS) to ensure reliable voltage regulation in distributed power systems with substantial Photovoltaic (PV) integration. The proposed method integrates grid sensitivity factor with Second-Order Cone Programming (SCOP) modeling for power flow. BESS’s optimal size and location are determined by minimizing the total cost of operation, voltage deviations, power losses, and peak demands in the distribution network. Additionally, the study explores the impact of Demand Response (DR) on BESS size and placement. The method’s effectiveness is demonstrated using a modified IEEE 33-bus system with actual load and PV generation data. By incorporating BESS’s optimal charging and discharging into traditional power flow analysis, grid parameters such as voltage and power flow accuracy are validated. Simulation results show the optimization model’s effectiveness, emphasizing the benefits of properly coordinating BESS in distribution systems with integrated PV. The numerical results indicate that the integration of BESS allocation with DR demonstrates that the proposed approach achieves a substantial reduction in energy losses (19 %), highlighting the effectiveness of the method in ensuring grid reliability under high PV penetration scenarios.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101738"},"PeriodicalIF":4.8,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098980","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

Robust optimization for optimal electrical asset placement in small and medium-sized industries 稳健的优化，最优的电力资产安置在中小型工业

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-13 DOI: 10.1016/j.segan.2025.101736

Pranay Kumar Saha, Anupam Trivedi, Dipti Srinivasan

{"title":"Robust optimization for optimal electrical asset placement in small and medium-sized industries","authors":"Pranay Kumar Saha, Anupam Trivedi, Dipti Srinivasan","doi":"10.1016/j.segan.2025.101736","DOIUrl":"10.1016/j.segan.2025.101736","url":null,"abstract":"<div><div>The increasing number and diversity of electricity-operated devices, machines, and equipment in small and medium-sized industries present significant challenges for energy arbitrage in supporting the main grid. These challenges include managing unpredictable load fluctuations, maintaining grid stability during peak demand, and balancing dynamic generation and consumption profiles. To address these issues, this study proposes integrating the system with new assets, which encompass controllable resources on both the generation and consumption sides—such as distributed renewable generation systems, electricity operated machine and equipment. The primary objective is to determine the optimal placement of these assets within industrial networks to maximize their efficiency in energy arbitrage operations. We employ robust optimization techniques that leverage historical operational data while accommodating uncertainties, including the maximum fluctuation rate in the generation and consumption of these assets, contracted capacity limits, and defined budgets of uncertainty. Comprehensive case studies demonstrate that optimal asset placement not only reduces operational costs and improves grid performance for industrial customers but also provides valuable insights for policymakers in formulating effective energy management strategies.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101736"},"PeriodicalIF":4.8,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144088942","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

Clustering electricity consumption patterns using functional data analysis 使用功能数据分析对电力消耗模式进行聚类

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-12 DOI: 10.1016/j.segan.2025.101742

Kangwon Seo , Hyeong Suk Na , Wonjae Lee , Cheng-Bang Chen , Sang Jin Kweon , Long Zhao , Soundar Kumara

{"title":"Clustering electricity consumption patterns using functional data analysis","authors":"Kangwon Seo , Hyeong Suk Na , Wonjae Lee , Cheng-Bang Chen , Sang Jin Kweon , Long Zhao , Soundar Kumara","doi":"10.1016/j.segan.2025.101742","DOIUrl":"10.1016/j.segan.2025.101742","url":null,"abstract":"<div><div>Investigating energy usage patterns in the commercial sector and identifying notable characteristics is imperative for implementing more flexible and effective demand-side management strategies, reducing energy costs, and improving energy efficiency. Properly clustering energy consumption patterns enables us to identify and distinguish major consumer groups and their energy load characteristics. This paper uses aggregated 3 years of smart meter data from approximately two thousand commercial customers to find major load profile clusters. Functional data analysis (FDA) is applied to the monthly aggregated power usage data to capture the dynamic and functional nature. The results show that the general amount of electricity usage, corresponding to the first functional principal component (FPC), dominates the function-to-function variability, and most of the remaining variability can be explained by three additional curve shape features, corresponding to the second through fourth FPCs. To account for the largely different scales and nonhomogeneous densities of the clustering variables, which are FPC scores, a multi-level nested clustering, a combination of the Gaussian mixture model and clustering tree, is performed. The resulting clusters are summarized by FPC scores, which easily characterize their consumption patterns, demonstrating the primary advantage of FDA.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101742"},"PeriodicalIF":4.8,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098978","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

Understanding the inception of 14.7 Hz oscillations emerging from a data center 了解从数据中心产生的14.7 Hz振荡的起源

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-12 DOI: 10.1016/j.segan.2025.101735

Chetan Mishra , Luigi Vanfretti , Jaime Delaree Jr. , T.J. Purcell , Kevin D. Jones

引用次数: 0

Demand response with load-block shifting in the day ahead scheduling of predominantly hydro systems: Impact on the large-scale Brazilian case 以水力发电为主的电力系统的日前调度中负荷块转移的需求响应：对巴西大型案例的影响

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-05-10 DOI: 10.1016/j.segan.2025.101728

Gabriel M. Longhi , Carmen L.T. Borges , André L. Diniz

{"title":"Demand response with load-block shifting in the day ahead scheduling of predominantly hydro systems: Impact on the large-scale Brazilian case","authors":"Gabriel M. Longhi , Carmen L.T. Borges , André L. Diniz","doi":"10.1016/j.segan.2025.101728","DOIUrl":"10.1016/j.segan.2025.101728","url":null,"abstract":"<div><div>Operational planning and scheduling of electrical systems aims to meet the system load in the most economical way, managing not only the risk of load curtailment but also to ensure ramping capability. Flexibility is also pursued by exploring the large penetration of variable renewable generation such as wind/solar plants. Demand response (DR) programs have emerged as an alternative to accommodate such variability by stimulating or paying customers to curtail or shift their load, yielding a reduction in peak prices and smoother hourly price curves. Even though the advantages of DR for originally pure thermal systems have been widely shown in the literature, quantification of the effects of DR optimization in predominantly hydro systems is yet to be better explored, since such systems already have a large flexibility in operation. We present a mixed integer linear programming application of DR with load-block shifting for the day ahead scheduling model of predominantly hydro systems, based on the official model that is used to dispatch and set system hourly prices for the Brazilian system. The model comprises load curtailment based on price offer by consumers, as well as load-block shifting, which consists in a more precise representation of loads that have time-shifting flexibility but not load profile flexibility. We show that the performance of the model is computationally feasible and assess its impact on marginal/total operation costs. We also evaluate some aspects such as: competition among offers and optimal bidding points from the customer´s point of view. Results are presented for the IEEE 14-bus system and the actual Brazilian hydrothermal-wind system.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"43 ","pages":"Article 101728"},"PeriodicalIF":4.8,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935655","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