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

Heat and power energy management of VPP with renewable sources and plug-in electric vehicle in energy and reserve market

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-27 DOI: 10.1016/j.segan.2025.101670

Jie Yu , Zihao Fu , Qingjie Zhang , Xiaoyu Chen , Jian Wang

{"title":"Heat and power energy management of VPP with renewable sources and plug-in electric vehicle in energy and reserve market","authors":"Jie Yu , Zihao Fu , Qingjie Zhang , Xiaoyu Chen , Jian Wang","doi":"10.1016/j.segan.2025.101670","DOIUrl":"10.1016/j.segan.2025.101670","url":null,"abstract":"<div><div>The virtual power plant (VPP) integrates electric vehicle (EV) parking lots as both flexible consumers and prosumer, leveraging their bidirectional charging capabilities to improve grid stability and profitability. This paper defines a novel method to the improve economic aspect of distributed energy resources (DERs) in a distribution network through a VPP framework, actively contributing in day-ahead and regulation reserve markets. One of the main novelties of this study is using a forecasted price-based unit commitment approach for VPPs in microgrids with the aim of determining an optimal pricing strategy though addressing real-world operational complexities. Also, this study integrates a dual-role EV parking lots, acting both as a consumer and electricity provider, and explores its potential to minimize costs while optimizing charging and discharging agendas. The proposed optimization model tries to obtain maximum VPP profits in day-ahead and reserve markets by controlling the complexities of distributed thermal and electrical production, energy storage limits, and power balance restraints. By implementing an efficient model based on the a mixed-integer linear programming (MILP), a higher solution speeds, global optimality, and scalability for larger problems overcoming traditional limitations such as local optima and infeasibility in large-scale scenarios is achieved. By considering the uncertainties of solar and wind sources, a spinning reservation technique is used to increase microgrid stability. This study also examines how demand response programs help gas stations operate better and facilitate effective energy transfers between VPPs and the upstream network. As a major step toward increasing microgrid profitability and operational efficiency, the results demonstrate the superiority of establishing a strategic pathway for VPPs to optimize energy transactions, set competitive reserve market pricing, and handle market uncertainties.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101670"},"PeriodicalIF":4.8,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552180","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

Network effects on the decoupling of carbon emissions in the power industry and power generation: A case study of China

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-25 DOI: 10.1016/j.segan.2025.101666

Muren BAI , Jia DONG , Cunbin LI

{"title":"Network effects on the decoupling of carbon emissions in the power industry and power generation: A case study of China","authors":"Muren BAI , Jia DONG , Cunbin LI","doi":"10.1016/j.segan.2025.101666","DOIUrl":"10.1016/j.segan.2025.101666","url":null,"abstract":"<div><div>The decoupling of carbon emissions in the power industry and power generation is of great significance to carbon emission reduction. In this paper, the network effect of the decoupling state was analyzed by applying the modified Gravity model and Social Network Analysis (SNA) approach, and finally the influencing factors of the spatial correlation between decoupling of carbon emissions in the power industry and power generation were analyzed by the quadratic assignment procedure (QAP)method. The results show that: (1) the decoupling effect of national carbon emissions in the power industry and power generation is significant, the decoupling states of the Northwest Grid is relatively smooth, and the decoupling status of the rest of the five major power grids is getting better.(2) Network associations in the decoupling state between regions become closer and closer, and the number of transmission relationships within clustered panels gradually increases, but there is an imbalance in the development within the network, with the North China Power Grid and the East China Power Grid as the centers of the network. (3) Geographic proximity, differences in economic level and population can significantly strengthen network formation, while differences in industrial structure and urbanization inhibit spatial network formation.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101666"},"PeriodicalIF":4.8,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534303","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 supply–demand optimization strategy for integrated energy system considering integrated demand response and electricity–heat–hydrogen hybrid energy storage 考虑综合需求响应和电-热-氢混合储能的综合能源系统供需优化策略

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-25 DOI: 10.1016/j.segan.2025.101658

Shaobo Shi , Qiang Gao , Yuehui Ji , Junjie Liu , Hao Chen , Yuchen Jiang

{"title":"A supply–demand optimization strategy for integrated energy system considering integrated demand response and electricity–heat–hydrogen hybrid energy storage","authors":"Shaobo Shi , Qiang Gao , Yuehui Ji , Junjie Liu , Hao Chen , Yuchen Jiang","doi":"10.1016/j.segan.2025.101658","DOIUrl":"10.1016/j.segan.2025.101658","url":null,"abstract":"<div><div>To address the reliability and stability of the supply–demand balance in integrated energy systems, a supply–demand optimization strategy that considers wind and photovoltaic power generation uncertainties and integrated demand response is proposed. On the supply side, a robust stochastic optimization model is developed to describe the uncertainty of wind and photovoltaic power output, considering the effect of time on the prediction error of wind and photovoltaic power output. Additionally, a electricity–heat–hydrogen hybrid energy storage model is developed to improve system flexibility by accounting for the lifetime loss of energy storage. On the demand side, a packaged demand-side management approach is proposed to incentivize user participation in integrated demand response. Finally, the supply–demand model is solved using the Karush–Kuhn–Tucker condition and the Big-M method. The simulation results show that the intraday revenue of the Energy Hub is increased by 17.22%, and the maximum intraday consumer surplus of the load aggregator is increased by 6.31%. The total cost of hybrid energy storage is reduced by 5.21%, and wind-photovoltaic utilization is increased by 2.1% compared to a single electric energy storage configuration. The total cost of hybrid energy storage is reduced by 4.26%, and wind-photovoltaic utilization is increased by 1.5% compared to the electric-heat storage combination. After considering the battery life, the configured capacity of the hybrid energy storage battery decreased by 10.06%.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101658"},"PeriodicalIF":4.8,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520403","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

Impact of thermal stores on multi-energy microgrids with multi-layer dynamic control architecture

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-25 DOI: 10.1016/j.segan.2025.101667

Pablo Horrillo-Quintero , Iván De la Cruz-Loredo , Pablo García-Triviño , Carlos E. Ugalde-Loo , Luis M. Fernández-Ramírez

{"title":"Impact of thermal stores on multi-energy microgrids with multi-layer dynamic control architecture","authors":"Pablo Horrillo-Quintero , Iván De la Cruz-Loredo , Pablo García-Triviño , Carlos E. Ugalde-Loo , Luis M. Fernández-Ramírez","doi":"10.1016/j.segan.2025.101667","DOIUrl":"10.1016/j.segan.2025.101667","url":null,"abstract":"<div><div>Thermal energy storage systems (TESSs) enhance multi-energy microgrids (MEMGs) operation by optimizing energy management. While previous research primarily focused on optimizing the MEMG operation using static MEMG models, this paper analyzes the dynamic impact of TESS on a grid-connected residential MEMG. This includes a photovoltaic plant, an electrical battery, and a hydrogen system with an electrolyzer, a fuel cell, and hydrogen tank. The thermal subsystem includes a gas boiler, a micro-combined heat and power (CHP) unit, an electric boiler, and a TESS tank. A novel intelligent control architecture based on fuzzy logic, model predictive control, and nonlinear optimization is presented to control the MEMG. Simulation results with TESS reveal a balanced heat production and demand, and improved temperature control. The integral time squared error (ITSE) is reduced by 91 % for the hot water circuit control and 81 % for the overall thermal balance of the MEMG. The improved control scheme also reduces the gas consumption, with a reduction of 12.44 % for the gas boiler, 1.81 % for the CHP, and 8.66 % in total, leading in turn to reduced operational costs (by 6 %) and CO<sub>2</sub> emissions (by 8.37 %) compared to the MEMG operation without a TESS under the same control scheme.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101667"},"PeriodicalIF":4.8,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512684","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

Machine learning approaches for the prediction of public EV charge point flexibility

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-24 DOI: 10.1016/j.segan.2025.101657

Federica Bellizio , Bart Dijkstra , Angelika Fertig , Jules Van Dijk , Philipp Heer

{"title":"Machine learning approaches for the prediction of public EV charge point flexibility","authors":"Federica Bellizio , Bart Dijkstra , Angelika Fertig , Jules Van Dijk , Philipp Heer","doi":"10.1016/j.segan.2025.101657","DOIUrl":"10.1016/j.segan.2025.101657","url":null,"abstract":"<div><div>The increasing number of electric vehicles on the road can play a key role as a source of flexibility for a reliable power system operation. Charge point operators, in particular, can adjust individual electric vehicle charging loads to provide system operators with aggregated energy flexibility, e.g. for congestion management, ancillary services or greenhouse gas emission reduction. However, managing individual charging sessions requires information about the expected session duration and energy demand, which are not available at the beginning of a session. In this work, a novel predictive workflow based on two causality-informed machine learning approaches with different levels of generalization is proposed to predict individual session duration and energy demand. Our key contributions include the development of a cluster-based predictive model for charge points and a user-based predictive model to capture individual charging behaviours, and the comparison of these models using a large-scale, real-world dataset. The proposed approaches were tested on real charging data provided by TotalEnergies, showing that considering user-specific charging behaviours enhances the accuracy performance by 16.1% and 37.9% for predictions of session duration and energy demand, respectively. By leveraging clustering and feature selection techniques, accounting for charge point- and user-specific charging patterns, and utilizing a large-scale real-world charging dataset, the proposed predictive workflow enables a comprehensive comparison of machine learning techniques in terms of accuracy performance when predicting public electric vehicle charge point flexibility.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101657"},"PeriodicalIF":4.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577721","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

Congestion-aware multi-objective scheduling and control for a user-centered EV charging hub

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-24 DOI: 10.1016/j.segan.2025.101656

Bart Nijenhuis, Gerwin Hoogsteen, Johann L. Hurink

{"title":"Congestion-aware multi-objective scheduling and control for a user-centered EV charging hub","authors":"Bart Nijenhuis, Gerwin Hoogsteen, Johann L. Hurink","doi":"10.1016/j.segan.2025.101656","DOIUrl":"10.1016/j.segan.2025.101656","url":null,"abstract":"<div><div>This paper presents a congestion-aware Energy Management System (EMS) for Electric Vehicle (EV) charging hubs with on-site PV generation and energy storage in the built environment. The concept of the system is based on a time-discretized scheduling approach that incorporates all relevant assets at the hub to charge the EVs without creating grid congestion problems. Since EV charging schedules in general have to be determined based on incomplete and often inaccurate forecasts and information, the scheduler is combined with an online control policy that operates to compensate for forecast errors or that can be used to react on external market price signals or congestion information. A simulation study of the scheduling concept and its underlying model shows that incorporating the current peak-tariff structure used in the Netherlands into the EMS can contribute to reducing the peak demand on the grid throughout the year for the proposed charging hub by 8.4%. The simulations furthermore show that the application of a peak shaving approach can lead to a peak load reduction of up to 36%, at only a 2.6% increase in total operational costs. The research objective of this study is to investigate how the theoretical model of the EMS can be applied in a real-world implementation. For this, the EMS is implemented in a real-life operational demonstration of the concept with real devices, data and users. The demonstration of the EMS in a real-world implementation advances the state of knowledge on these topics by demonstrating conflicting interests the lack of information-exchange between different stakeholders and the effect of this on the EV charging ecosystem. Further research is necessary, specifically on the interaction between EVs, Charge Point Operators, Mobility Service Providers and other relevant market parties such as energy traders.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101656"},"PeriodicalIF":4.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520401","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

Modelling the influence of atmospheric conditions represented by wind, precipitation and air temperature on the intensity of failure and restoration time of medium-voltage power lines

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-24 DOI: 10.1016/j.segan.2025.101652

Andrzej Ł. Chojnacki

引用次数: 0

A fully adaptive distributionally robust multistage framework based on mixed decision rules for wind-thermal system operation under uncertainty 基于混合决策规则的完全自适应分布式稳健多阶段框架，用于不确定条件下的风热系统运行

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-21 DOI: 10.1016/j.segan.2025.101664

Ying Yang , Linfeng Yang , Xinwei Shen , Zhaoyang Dong

{"title":"A fully adaptive distributionally robust multistage framework based on mixed decision rules for wind-thermal system operation under uncertainty","authors":"Ying Yang , Linfeng Yang , Xinwei Shen , Zhaoyang Dong","doi":"10.1016/j.segan.2025.101664","DOIUrl":"10.1016/j.segan.2025.101664","url":null,"abstract":"<div><div>The growing integration of renewable energy into power systems offers opportunities for achieving low-cost and sustainable energy supplies. However, its intermittency poses technical challenges, necessitating flexible and reliable decision-making methods. This study aims to develop a framework to enhance the integration of wind power while ensuring system reliability and minimizing costs. A fully adaptive distributionally robust multistage framework is proposed, leveraging mixed decision rules to enable dynamic and efficient use of quick-start units and generation dispatch. The improved mixed decision rules expand the feasible region and handle higher dimensional variables, are first introduced in such problem. Advanced optimization techniques are employed to reformulate the framework into mixed integer linear programming, ensuring computational tractability. The introduction of improved mixed decision rules with distributionally robust optimization and the solvable reformulation of the framework highlight the novelty of this work. Case studies on IEEE test systems demonstrate the framework’s superiority over traditional models by increasing wind power penetration, reducing fossil fuel consumption, and providing feasible and optimal solutions in uncertain environments.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101664"},"PeriodicalIF":4.8,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520402","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

Design of P2P coordinative transaction mechanism considering low-carbon preference of multiple prosumers in regional electricity market

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-20 DOI: 10.1016/j.segan.2025.101661

Yue Guan, Qiang Hou, Shiquan Wang

{"title":"Design of P2P coordinative transaction mechanism considering low-carbon preference of multiple prosumers in regional electricity market","authors":"Yue Guan, Qiang Hou, Shiquan Wang","doi":"10.1016/j.segan.2025.101661","DOIUrl":"10.1016/j.segan.2025.101661","url":null,"abstract":"<div><div>The market-oriented trading of distributed energy with the participation of multiple prosumers has gradually become a solution to promote the consumption of distributed energy. The transaction preferences of prosumers have a significant impact on market transaction efficiency. How to design a market transaction mechanism that considers the transaction preferences of prosumers to promote efficiency improvement has become a current research hotspot. In this paper: firstly, a regional electricity market trading framework with the participation of multiple prosumers at the distribution network level was established; Secondly, the internal resources of prosumers were analyzed, and the mathematical models of their output units and loads were constructed; Thirdly, a peer-to-peer (P2P) transaction mechanism for regional electricity market was designed based on the combinatorial double auction theory, which takes into account different energy demands and low-carbon preferences of prosumers, among them, with the goal of minimizing operating costs during the scheduling cycle of prosumers, the internal resources were coordinated to achieve balance and their energy supply - demand plans were obtained (as their bidding electricity quantity), and on the basis of considering the low-carbon preferences, a Supply Function Equilibrium (SFE) model was adopted to construct their bidding price strategy (as their bidding electricity price). Third party auctioneer was used to coordinate P2P transactions between prosumers, and different bidding types were introduced to accurately express prosumers´ different energy demands during the trading process. Finally, the effectiveness and feasibility of the proposed P2P transaction mechanism were verified through numerical examples.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101661"},"PeriodicalIF":4.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479049","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

Critical component analysis of cyber-physical power systems in cascading failures using graph convolutional networks: An energy-based approach

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-19 DOI: 10.1016/j.segan.2025.101653

Sajedeh Soleimani, Ahmad Afshar, Hajar Atrianfar

{"title":"Critical component analysis of cyber-physical power systems in cascading failures using graph convolutional networks: An energy-based approach","authors":"Sajedeh Soleimani, Ahmad Afshar, Hajar Atrianfar","doi":"10.1016/j.segan.2025.101653","DOIUrl":"10.1016/j.segan.2025.101653","url":null,"abstract":"<div><div>Power systems, with increasing integration into communication networks, have evolved to become complex and interdependent cyber–physical power systems that are highly vulnerable to cascading failures. These failures, due to their propagation through the cyber and physical networks, often lead to severe disruptions. We employ improved percolation theory to model cascading failures triggered by malware cyber-attacks. Addressing the vulnerability of CPPS requires a comprehensive analysis that spans both the structural and functional dimensions of CPPS. This paper introduces a novel framework for vulnerability assessment in CPPS using Graph Convolutional Networks (GCN). Our approach captures the topological complexities and dynamic characteristics of CPPS, incorporating the entropy of potential energy of power system as a new feature to predict and analyze failure propagation. Through Layer-wise Relevance Propagation (LRP), we subsequently quantify the influence of potential energy on system vulnerabilities. Critical components are identified by using LRP scores and an entropy weighting method (EWM). Simulation results based on the cyber–physical IEEE 39-bus and IEEE RTS-96 power systems as test cases, demonstrate the model’s efficacy in identifying vulnerable nodes and branches and highlight the significant role of potential energy in cascading failures. This framework provides a comprehensive approach for real-time vulnerability assessments and resilience enhancement in CPPS.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101653"},"PeriodicalIF":4.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464390","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