{"title":"基于CVaR的最不发达国家购电组合优化模型","authors":"Hailun Huang, Zheng Yan, Yunhe Hou","doi":"10.1109/ICPST.2008.4745232","DOIUrl":null,"url":null,"abstract":"Based on the CVaR theory in financial risk field, a novel electricity-procurement portfolio optimization model for a local distribution company (LDC) is proposed, considering the risk and expected purchase cost synthetically. The conditional value at risk (CVaR) is used as the risk measurement index. The new model is applied to determine the electricity allocation ratio and efficient frontiers for the LDC in three markets. Simulation results demonstrate that the proposed model is correct, and it can guarantee the LDC to bear the minimum CVaR risk within a certain expected purchase cost. It provides an effective way for the LDC to make purchase decision and manage risks.","PeriodicalId":107016,"journal":{"name":"2008 Joint International Conference on Power System Technology and IEEE Power India Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Novel CVaR Based Portfolio Optimization Model for LDC Electricity Procurement\",\"authors\":\"Hailun Huang, Zheng Yan, Yunhe Hou\",\"doi\":\"10.1109/ICPST.2008.4745232\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the CVaR theory in financial risk field, a novel electricity-procurement portfolio optimization model for a local distribution company (LDC) is proposed, considering the risk and expected purchase cost synthetically. The conditional value at risk (CVaR) is used as the risk measurement index. The new model is applied to determine the electricity allocation ratio and efficient frontiers for the LDC in three markets. Simulation results demonstrate that the proposed model is correct, and it can guarantee the LDC to bear the minimum CVaR risk within a certain expected purchase cost. It provides an effective way for the LDC to make purchase decision and manage risks.\",\"PeriodicalId\":107016,\"journal\":{\"name\":\"2008 Joint International Conference on Power System Technology and IEEE Power India Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Joint International Conference on Power System Technology and IEEE Power India Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPST.2008.4745232\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Joint International Conference on Power System Technology and IEEE Power India Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPST.2008.4745232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel CVaR Based Portfolio Optimization Model for LDC Electricity Procurement
Based on the CVaR theory in financial risk field, a novel electricity-procurement portfolio optimization model for a local distribution company (LDC) is proposed, considering the risk and expected purchase cost synthetically. The conditional value at risk (CVaR) is used as the risk measurement index. The new model is applied to determine the electricity allocation ratio and efficient frontiers for the LDC in three markets. Simulation results demonstrate that the proposed model is correct, and it can guarantee the LDC to bear the minimum CVaR risk within a certain expected purchase cost. It provides an effective way for the LDC to make purchase decision and manage risks.