{"title":"加强配电网向智能电网发展:电压控制问题","authors":"A. D. Fazio, G. Fusco, M. Russo","doi":"10.1109/CDC.2013.6760989","DOIUrl":null,"url":null,"abstract":"The evolution of existing distribution systems toward smart grids requires the exploitation of all the capabilities of the new Distributed Generation (DG). To this aim, the present paper addresses the problem of improving the voltage profile regulation in distribution networks with DG. According to a decentralized approach, the set-point of a reactive power regulation scheme of the DG is designed in an optimal sense by solving a constrained minimization problem. Since the proposed design uses only local measurements new investments on the existing networks are limited. The results of numerical simulations are provided for a MV multiple-feeder distribution system with multiple DGs with reference to two different optimization objectives.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"184 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Enhancing distribution networks to evolve toward smart grids: The voltage control problem\",\"authors\":\"A. D. Fazio, G. Fusco, M. Russo\",\"doi\":\"10.1109/CDC.2013.6760989\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The evolution of existing distribution systems toward smart grids requires the exploitation of all the capabilities of the new Distributed Generation (DG). To this aim, the present paper addresses the problem of improving the voltage profile regulation in distribution networks with DG. According to a decentralized approach, the set-point of a reactive power regulation scheme of the DG is designed in an optimal sense by solving a constrained minimization problem. Since the proposed design uses only local measurements new investments on the existing networks are limited. The results of numerical simulations are provided for a MV multiple-feeder distribution system with multiple DGs with reference to two different optimization objectives.\",\"PeriodicalId\":415568,\"journal\":{\"name\":\"52nd IEEE Conference on Decision and Control\",\"volume\":\"184 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"52nd IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2013.6760989\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"52nd IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2013.6760989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancing distribution networks to evolve toward smart grids: The voltage control problem
The evolution of existing distribution systems toward smart grids requires the exploitation of all the capabilities of the new Distributed Generation (DG). To this aim, the present paper addresses the problem of improving the voltage profile regulation in distribution networks with DG. According to a decentralized approach, the set-point of a reactive power regulation scheme of the DG is designed in an optimal sense by solving a constrained minimization problem. Since the proposed design uses only local measurements new investments on the existing networks are limited. The results of numerical simulations are provided for a MV multiple-feeder distribution system with multiple DGs with reference to two different optimization objectives.