{"title":"基于日前运行规划的风电弃风优化","authors":"Rui Alves, F. Reis, Hong Shen","doi":"10.1109/ISGTEurope.2016.7856216","DOIUrl":null,"url":null,"abstract":"In this paper a day-ahead operational planning methodology, for deciding how much wind power to curtail and where, is presented in order to support the wind power curtailment decision-making by system operators under scenarios of network bottlenecks. The Evolutionary Particle Swarm Optimization algorithm is used to provide robust wind power curtailment solutions at minimum cost. The methodology is validated on a case-study based on the Portuguese transmission system. Obtained results show the capability of the methodology to achieve near optimal curtailment solutions when applied to large-scale power systems.","PeriodicalId":330869,"journal":{"name":"2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"113 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Wind power curtailment optimization for day-ahead operational planning\",\"authors\":\"Rui Alves, F. Reis, Hong Shen\",\"doi\":\"10.1109/ISGTEurope.2016.7856216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a day-ahead operational planning methodology, for deciding how much wind power to curtail and where, is presented in order to support the wind power curtailment decision-making by system operators under scenarios of network bottlenecks. The Evolutionary Particle Swarm Optimization algorithm is used to provide robust wind power curtailment solutions at minimum cost. The methodology is validated on a case-study based on the Portuguese transmission system. Obtained results show the capability of the methodology to achieve near optimal curtailment solutions when applied to large-scale power systems.\",\"PeriodicalId\":330869,\"journal\":{\"name\":\"2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)\",\"volume\":\"113 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISGTEurope.2016.7856216\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEurope.2016.7856216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wind power curtailment optimization for day-ahead operational planning
In this paper a day-ahead operational planning methodology, for deciding how much wind power to curtail and where, is presented in order to support the wind power curtailment decision-making by system operators under scenarios of network bottlenecks. The Evolutionary Particle Swarm Optimization algorithm is used to provide robust wind power curtailment solutions at minimum cost. The methodology is validated on a case-study based on the Portuguese transmission system. Obtained results show the capability of the methodology to achieve near optimal curtailment solutions when applied to large-scale power systems.