Yizhe Xie, Kai Xing, Lizi Luo, Shuai Lu, Cheng Chen, Xiaoming Wang, Wenguang Zhao, Mert Korkali
{"title":"在有季节性负荷的配电系统中协同部署多种加固方法以降低网络损耗","authors":"Yizhe Xie, Kai Xing, Lizi Luo, Shuai Lu, Cheng Chen, Xiaoming Wang, Wenguang Zhao, Mert Korkali","doi":"10.1049/enc2.12128","DOIUrl":null,"url":null,"abstract":"<p>The integration of seasonal loads, such as cereal baking and aquatic-product processing loads, often leads to significant voltage deviations and severe peak loads of the distribution system during specific periods, resulting in increased network losses. Traditional approaches for reducing network losses are becoming less effective and cost-efficient due to the spatiotemporally uneven distribution characteristics of seasonal loads. To address this issue, this study proposes an optimisation model that collaboratively integrates mobile energy storage, switching capacitors, and tie lines to minimise annual network losses in special planning scenarios affected by seasonal loads. The deployment strategies of multiple reinforcement methods are thoroughly analysed, greatly enhancing the explainability and feasibility of the collaborative deployment model. Then, the proposed model is reformulated to a mixed-integer linear programming model using the inscribed regular dodecagon approximation approach, thereby making it trackable for state-of-the-art solvers. To illustrate the effectiveness of the model, case studies are conducted on a unique 55-bus distribution system located in East China, which contains feeders with substantial seasonal variation aquaculture loads and with general loads. The effectiveness of multiple reinforcement methods is thoroughly analysed through detailed numerical results. Furthermore, a sensitivity analysis of the investment budget is conducted.</p>","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"5 5","pages":"301-315"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.12128","citationCount":"0","resultStr":"{\"title\":\"Collaborative deployment of multiple reinforcement methods for network-loss reduction in distribution system with seasonal loads\",\"authors\":\"Yizhe Xie, Kai Xing, Lizi Luo, Shuai Lu, Cheng Chen, Xiaoming Wang, Wenguang Zhao, Mert Korkali\",\"doi\":\"10.1049/enc2.12128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The integration of seasonal loads, such as cereal baking and aquatic-product processing loads, often leads to significant voltage deviations and severe peak loads of the distribution system during specific periods, resulting in increased network losses. Traditional approaches for reducing network losses are becoming less effective and cost-efficient due to the spatiotemporally uneven distribution characteristics of seasonal loads. To address this issue, this study proposes an optimisation model that collaboratively integrates mobile energy storage, switching capacitors, and tie lines to minimise annual network losses in special planning scenarios affected by seasonal loads. The deployment strategies of multiple reinforcement methods are thoroughly analysed, greatly enhancing the explainability and feasibility of the collaborative deployment model. Then, the proposed model is reformulated to a mixed-integer linear programming model using the inscribed regular dodecagon approximation approach, thereby making it trackable for state-of-the-art solvers. To illustrate the effectiveness of the model, case studies are conducted on a unique 55-bus distribution system located in East China, which contains feeders with substantial seasonal variation aquaculture loads and with general loads. The effectiveness of multiple reinforcement methods is thoroughly analysed through detailed numerical results. Furthermore, a sensitivity analysis of the investment budget is conducted.</p>\",\"PeriodicalId\":100467,\"journal\":{\"name\":\"Energy Conversion and Economics\",\"volume\":\"5 5\",\"pages\":\"301-315\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.12128\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Conversion and Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/enc2.12128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Conversion and Economics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/enc2.12128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Collaborative deployment of multiple reinforcement methods for network-loss reduction in distribution system with seasonal loads
The integration of seasonal loads, such as cereal baking and aquatic-product processing loads, often leads to significant voltage deviations and severe peak loads of the distribution system during specific periods, resulting in increased network losses. Traditional approaches for reducing network losses are becoming less effective and cost-efficient due to the spatiotemporally uneven distribution characteristics of seasonal loads. To address this issue, this study proposes an optimisation model that collaboratively integrates mobile energy storage, switching capacitors, and tie lines to minimise annual network losses in special planning scenarios affected by seasonal loads. The deployment strategies of multiple reinforcement methods are thoroughly analysed, greatly enhancing the explainability and feasibility of the collaborative deployment model. Then, the proposed model is reformulated to a mixed-integer linear programming model using the inscribed regular dodecagon approximation approach, thereby making it trackable for state-of-the-art solvers. To illustrate the effectiveness of the model, case studies are conducted on a unique 55-bus distribution system located in East China, which contains feeders with substantial seasonal variation aquaculture loads and with general loads. The effectiveness of multiple reinforcement methods is thoroughly analysed through detailed numerical results. Furthermore, a sensitivity analysis of the investment budget is conducted.