{"title":"微电网存储系统第三方投资规模与时机的目标规划方法","authors":"Hisham Alharbi, Kankar Bhattacharya","doi":"10.1109/EPEC.2018.8598299","DOIUrl":null,"url":null,"abstract":"In this paper, investment decisions on storage system installations by a third-party investor in a microgrid is studied. The optimal storage power rating, energy capacity, and the year of installation are determined while maximizing the investor's profit and simultaneously minimizing the microigrd operational cost. The multi-objective problem is solved using a goal programming approach with a weight assigned to each objective. The energy storage is modeled to participate in energy arbitrage and provisions for operating reserves to the microgrid. The storage system performance parameters are considered, and its capacity degradation over the planning horizon is modeled. The results show the effectiveness of the proposed approach and demonstrate the storage system investment decisions in different microgrid operational scenarios.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Goal Programming Approach to Sizing and Timing of Third Party Investments in Storage System for Microgrids\",\"authors\":\"Hisham Alharbi, Kankar Bhattacharya\",\"doi\":\"10.1109/EPEC.2018.8598299\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, investment decisions on storage system installations by a third-party investor in a microgrid is studied. The optimal storage power rating, energy capacity, and the year of installation are determined while maximizing the investor's profit and simultaneously minimizing the microigrd operational cost. The multi-objective problem is solved using a goal programming approach with a weight assigned to each objective. The energy storage is modeled to participate in energy arbitrage and provisions for operating reserves to the microgrid. The storage system performance parameters are considered, and its capacity degradation over the planning horizon is modeled. The results show the effectiveness of the proposed approach and demonstrate the storage system investment decisions in different microgrid operational scenarios.\",\"PeriodicalId\":265297,\"journal\":{\"name\":\"2018 IEEE Electrical Power and Energy Conference (EPEC)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Electrical Power and Energy Conference (EPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPEC.2018.8598299\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Electrical Power and Energy Conference (EPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2018.8598299","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Goal Programming Approach to Sizing and Timing of Third Party Investments in Storage System for Microgrids
In this paper, investment decisions on storage system installations by a third-party investor in a microgrid is studied. The optimal storage power rating, energy capacity, and the year of installation are determined while maximizing the investor's profit and simultaneously minimizing the microigrd operational cost. The multi-objective problem is solved using a goal programming approach with a weight assigned to each objective. The energy storage is modeled to participate in energy arbitrage and provisions for operating reserves to the microgrid. The storage system performance parameters are considered, and its capacity degradation over the planning horizon is modeled. The results show the effectiveness of the proposed approach and demonstrate the storage system investment decisions in different microgrid operational scenarios.