IET Generation, Transmission & Distribution最新文献

A robust optimization approach for resiliency improvement in power distribution system 提高配电系统恢复能力的稳健优化方法

IET Generation, Transmission & Distribution Pub Date : 2024-02-14 DOI: 10.1049/gtd2.13062

Reza Abshirini, Mojtaba Najafi, Naghi Moaddabi Pirkolachahi

{"title":"A robust optimization approach for resiliency improvement in power distribution system","authors":"Reza Abshirini, Mojtaba Najafi, Naghi Moaddabi Pirkolachahi","doi":"10.1049/gtd2.13062","DOIUrl":"https://doi.org/10.1049/gtd2.13062","url":null,"abstract":"The occurrence of natural disasters has led to an alarming increase in power interruptions, with severe impacts. Compounding this problem is the uncertain nature of data, which presents significant challenges in enhancing the resiliency of power distribution systems following such events. To tackle these issues, this paper introduces a robust optimization approach for improving the resiliency of power distribution systems. The approach encompasses crew teams for switching actions as part of the restoration process, along with demand response programs and mobile generators (MGs). By simultaneously leveraging these elements and considering the uncertainty associated with electrical load and electrical price, the resiliency of the system is enhanced. The objective function is tri‐level, comprising minimum, maximum, and minimum functions. At the first level, the approach minimizes the cost of commitment of combined heat and power plants (CHPs) by taking into account the location of MGs and the reconfiguration structure in power distribution systems. The second level aims to identify the worst‐case scenario for the uncertainty variables. Finally, the third level focuses on minimizing the total operation cost under the worst‐case scenario using demand response programs. The proposed algorithm is implemented on an IEEE 33‐bus test distribution system, with four different cases investigated.","PeriodicalId":510347,"journal":{"name":"IET Generation, Transmission & Distribution","volume":"524 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139839049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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 a novel neuro‐adaptive excitation control system for power systems 设计用于电力系统的新型神经自适应励磁控制系统

IET Generation, Transmission & Distribution Pub Date : 2024-02-14 DOI: 10.1049/gtd2.13102

Lionel Leroy Sonfack, René Kuaté-Fochie, A. M. Fombu, Rostand Marc Douanla, Arnaud Flanclair Tchouani Njomo, G. Kenné

引用次数: 0

Pseudo‐measurement‐based state estimation for railway power supply systems with renewable energy resources 基于伪测量的可再生能源铁路供电系统状态估计

IET Generation, Transmission & Distribution Pub Date : 2024-02-06 DOI: 10.1049/gtd2.13120

Zheng Pan, Liang Che, Chunming Tu

{"title":"Pseudo‐measurement‐based state estimation for railway power supply systems with renewable energy resources","authors":"Zheng Pan, Liang Che, Chunming Tu","doi":"10.1049/gtd2.13120","DOIUrl":"https://doi.org/10.1049/gtd2.13120","url":null,"abstract":"State estimation is critical for railway power supply systems (RPSSs). Pseudo‐measurement is commonly used in state estimation. However, the fluctuations of renewable generations and railway traction loads in RPSS may introduce data noise, which will jeopardize the accuracy of the generated pseudo‐measurements and thus impact the state estimation. Additionally, when learning the historical measurement data sequences, the traditional pseudo‐measurement model is likely to have overfitting, which will further impact the accuracy of pseudo‐measurements, thereby affecting the accuracy of state estimation. To address these issues, this paper proposes a high‐accuracy pseudo‐measurement‐based state estimation approach for RPSSs. Firstly, a denoising autoencoder‐based method is used to mitigate the impact of data noise on the accuracy of pseudo measurements, and a gated recurrent unit‐based method is used to adaptively learn the historical measurement data sequence, thereby improving the accuracy of pseudo measurements. Next, the pseudo‐measurement weights are obtained by generating pseudo‐measurement variances using the Gaussian mixture model. Finally, the pseudo measurements and real‐time measurements are integrated by weighted least squares to realize the state estimation of RPSS. The effectiveness and accuracy of the proposed method are verified by simulation on a modified IEEE 33‐node system which includes a railway traction substation and renewable generations.","PeriodicalId":510347,"journal":{"name":"IET Generation, Transmission & Distribution","volume":"190 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139861376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi‐layer–multi‐player game model in electricity market 电力市场中的多层多玩家博弈模型

IET Generation, Transmission & Distribution Pub Date : 2024-02-02 DOI: 10.1049/gtd2.13125

Hajar Kafshian, Mohammad Ali Saniee Monfared

{"title":"A multi‐layer–multi‐player game model in electricity market","authors":"Hajar Kafshian, Mohammad Ali Saniee Monfared","doi":"10.1049/gtd2.13125","DOIUrl":"https://doi.org/10.1049/gtd2.13125","url":null,"abstract":"Here, a novel tri‐level energy market model aimed at addressing the challenges posed by demand side management (DSM) in the electricity distribution company (EDC) is introduced. DSM has emerged as a new strategy employed by EDCs to manage and control electricity demand by encouraging end‐users to modify their electricity consumption patterns. This is achieved through the participation of demand response (DR) aggregators, which play a crucial role in assisting end‐users with strategies and technologies to reduce their electricity consumption during peak hours. The proposed tri‐level energy market model consists of four distinct players: EDC, microgrids, aggregators, customers. The interactions between these four actors are modelled within a tri‐level game framework, where the EDC and aggregators act as leaders, and the micro‐grids and customers are followers. This multi‐level and multi‐player game structure allows for a more realistic representation of the complexities involved in DSM programs within the energy market. To demonstrate the effectiveness of the proposed model, a real case study is utilized, showing that the new model better resembles real‐life market conditions. The results illustrate how the tri‐level energy market model can significantly reduce demand fluctuations during peak hours, leading to improved efficiency and effectiveness within DSM programs.","PeriodicalId":510347,"journal":{"name":"IET Generation, Transmission & Distribution","volume":"94 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139809458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IET Generation, Transmission &amp; Distribution最新文献

IET Generation, Transmission & Distribution最新文献