{"title":"分布式发电组合插入策略的多目标优化","authors":"G. A. Brigatto, C. Carmargo, E. T. Sica","doi":"10.1109/TDC-LA.2010.5762947","DOIUrl":null,"url":null,"abstract":"In this paper, an optimal insertion strategy model of power plant units from a Distributed Generation portfolio is proposed. The study is based on a multiobjective formulation involving economical, technical and environmental aspects, and it consists of determining the quantity of units of each power plant that will be inserted in a distribution network by planning stage, considering some known specifications, expansion sceneries and constraints. The modeling aims to obtain a Pareto frontier set of solutions, which is addressed utilizing a multiobjective Particle Swarm algorithm and the Maximin metric. An application example is presented to test the proposed procedure; a metric to measure the diversity of the obtained frontier is employed, and the Max-Min approach is used as decision criterion.","PeriodicalId":222318,"journal":{"name":"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Multiobjective optimization of distributed generation portfolio insertion strategies\",\"authors\":\"G. A. Brigatto, C. Carmargo, E. T. Sica\",\"doi\":\"10.1109/TDC-LA.2010.5762947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an optimal insertion strategy model of power plant units from a Distributed Generation portfolio is proposed. The study is based on a multiobjective formulation involving economical, technical and environmental aspects, and it consists of determining the quantity of units of each power plant that will be inserted in a distribution network by planning stage, considering some known specifications, expansion sceneries and constraints. The modeling aims to obtain a Pareto frontier set of solutions, which is addressed utilizing a multiobjective Particle Swarm algorithm and the Maximin metric. An application example is presented to test the proposed procedure; a metric to measure the diversity of the obtained frontier is employed, and the Max-Min approach is used as decision criterion.\",\"PeriodicalId\":222318,\"journal\":{\"name\":\"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)\",\"volume\":\"193 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TDC-LA.2010.5762947\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDC-LA.2010.5762947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiobjective optimization of distributed generation portfolio insertion strategies
In this paper, an optimal insertion strategy model of power plant units from a Distributed Generation portfolio is proposed. The study is based on a multiobjective formulation involving economical, technical and environmental aspects, and it consists of determining the quantity of units of each power plant that will be inserted in a distribution network by planning stage, considering some known specifications, expansion sceneries and constraints. The modeling aims to obtain a Pareto frontier set of solutions, which is addressed utilizing a multiobjective Particle Swarm algorithm and the Maximin metric. An application example is presented to test the proposed procedure; a metric to measure the diversity of the obtained frontier is employed, and the Max-Min approach is used as decision criterion.