{"title":"考虑多个N-1-1事件的两阶段随机电网扩展","authors":"Daniel A. Zuniga Vazquez, Neng Fan","doi":"10.1109/NAPS46351.2019.9000326","DOIUrl":null,"url":null,"abstract":"A reliable power system expansion planning may be achieved by placing new transmission lines and generation units while checking the grid's survivability under different contingency scenarios with defined probabilities. This paper considers a stochastic optimization approach for the reliable expansion planning of a power system with a compliance check on economic dispatch and power flows under $N-1-1$ contingencies with corrective actions. This yields a complex large-scale mixed-integer linear programming (MILP) optimization problem. For an efficient solution, a Benders Decomposition algorithm is adapted. The algorithm and model are assessed on modified versions of IEEE test systems, and computational experiments are performed to validate the effectiveness of the proposed method.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Two-Stage Stochastic Power Grid Expansion Considering Multiple N-1-1 Contingencies\",\"authors\":\"Daniel A. Zuniga Vazquez, Neng Fan\",\"doi\":\"10.1109/NAPS46351.2019.9000326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A reliable power system expansion planning may be achieved by placing new transmission lines and generation units while checking the grid's survivability under different contingency scenarios with defined probabilities. This paper considers a stochastic optimization approach for the reliable expansion planning of a power system with a compliance check on economic dispatch and power flows under $N-1-1$ contingencies with corrective actions. This yields a complex large-scale mixed-integer linear programming (MILP) optimization problem. For an efficient solution, a Benders Decomposition algorithm is adapted. The algorithm and model are assessed on modified versions of IEEE test systems, and computational experiments are performed to validate the effectiveness of the proposed method.\",\"PeriodicalId\":175719,\"journal\":{\"name\":\"2019 North American Power Symposium (NAPS)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS46351.2019.9000326\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS46351.2019.9000326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Two-Stage Stochastic Power Grid Expansion Considering Multiple N-1-1 Contingencies
A reliable power system expansion planning may be achieved by placing new transmission lines and generation units while checking the grid's survivability under different contingency scenarios with defined probabilities. This paper considers a stochastic optimization approach for the reliable expansion planning of a power system with a compliance check on economic dispatch and power flows under $N-1-1$ contingencies with corrective actions. This yields a complex large-scale mixed-integer linear programming (MILP) optimization problem. For an efficient solution, a Benders Decomposition algorithm is adapted. The algorithm and model are assessed on modified versions of IEEE test systems, and computational experiments are performed to validate the effectiveness of the proposed method.