{"title":"基于可再生能源集成和系统柔性研究的随机生产仿真模型","authors":"Shucheng Liu, Wenxiong Huang, Yi Zhang","doi":"10.1109/PMAPS.2016.7764099","DOIUrl":null,"url":null,"abstract":"A stochastic production simulation model was developed to evaluate the California Independent System Operator (CAISO) system capacity and flexibility sufficiency in order to integrate high volume of renewable generation to meet the California state renewables portfolio standard (RPS) goals. The model, which simulates the operation of the CAISO system, uses four stochastic variables, generation resource forced outages, load, solar and wind generation, to capture a wide range of possible system conditions. A novel pattern preserving methodology was developed to create samples of stochastic load, solar and wind generation variables. The model was used to study the system capacity and flexibility needs to integrate 33% renewable generation in California. The results of this study were filed to the California Public Utilities Commission (CPUC) in the Long Term Procurement Plan (LTPP) proceeding.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A stochastic production simulation model for renewable integration and system flexibility studies\",\"authors\":\"Shucheng Liu, Wenxiong Huang, Yi Zhang\",\"doi\":\"10.1109/PMAPS.2016.7764099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A stochastic production simulation model was developed to evaluate the California Independent System Operator (CAISO) system capacity and flexibility sufficiency in order to integrate high volume of renewable generation to meet the California state renewables portfolio standard (RPS) goals. The model, which simulates the operation of the CAISO system, uses four stochastic variables, generation resource forced outages, load, solar and wind generation, to capture a wide range of possible system conditions. A novel pattern preserving methodology was developed to create samples of stochastic load, solar and wind generation variables. The model was used to study the system capacity and flexibility needs to integrate 33% renewable generation in California. The results of this study were filed to the California Public Utilities Commission (CPUC) in the Long Term Procurement Plan (LTPP) proceeding.\",\"PeriodicalId\":265474,\"journal\":{\"name\":\"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PMAPS.2016.7764099\",\"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 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PMAPS.2016.7764099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A stochastic production simulation model for renewable integration and system flexibility studies
A stochastic production simulation model was developed to evaluate the California Independent System Operator (CAISO) system capacity and flexibility sufficiency in order to integrate high volume of renewable generation to meet the California state renewables portfolio standard (RPS) goals. The model, which simulates the operation of the CAISO system, uses four stochastic variables, generation resource forced outages, load, solar and wind generation, to capture a wide range of possible system conditions. A novel pattern preserving methodology was developed to create samples of stochastic load, solar and wind generation variables. The model was used to study the system capacity and flexibility needs to integrate 33% renewable generation in California. The results of this study were filed to the California Public Utilities Commission (CPUC) in the Long Term Procurement Plan (LTPP) proceeding.