{"title":"储能与可再生分布式发电的联合分配方法","authors":"V. Kalkhambkar, R. Kumar, R. Bhakar","doi":"10.1109/ICRAIE.2016.7939471","DOIUrl":null,"url":null,"abstract":"This paper presents a methodology for joint optimal allocation of energy storage (ES) and renewable distributed generation (RDG) for energy loss minimization. The paper also justifies the necessity of joint optimal allocation of ES and RDG. All possible sixteen combinations of design variables of RDG and ES are analyzed for the joint optimal allocation. The paper proposes a probabilistic generation model for solar DG and wind DG. This generation model and IEEE-RTS based load model are integrated into an optimal power flow along with energy storage. The non-linear constrained optimization problem is solved by robust and high-performance metaheuristic, symbiotic organisms search (SOS) optimization. Case studies are performed on a typical 34 - bus test system using MATLAB®","PeriodicalId":400935,"journal":{"name":"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Methodology for joint allocation of energy storage and renewable distributed generation\",\"authors\":\"V. Kalkhambkar, R. Kumar, R. Bhakar\",\"doi\":\"10.1109/ICRAIE.2016.7939471\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a methodology for joint optimal allocation of energy storage (ES) and renewable distributed generation (RDG) for energy loss minimization. The paper also justifies the necessity of joint optimal allocation of ES and RDG. All possible sixteen combinations of design variables of RDG and ES are analyzed for the joint optimal allocation. The paper proposes a probabilistic generation model for solar DG and wind DG. This generation model and IEEE-RTS based load model are integrated into an optimal power flow along with energy storage. The non-linear constrained optimization problem is solved by robust and high-performance metaheuristic, symbiotic organisms search (SOS) optimization. Case studies are performed on a typical 34 - bus test system using MATLAB®\",\"PeriodicalId\":400935,\"journal\":{\"name\":\"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRAIE.2016.7939471\",\"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 Recent Advances and Innovations in Engineering (ICRAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAIE.2016.7939471","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Methodology for joint allocation of energy storage and renewable distributed generation
This paper presents a methodology for joint optimal allocation of energy storage (ES) and renewable distributed generation (RDG) for energy loss minimization. The paper also justifies the necessity of joint optimal allocation of ES and RDG. All possible sixteen combinations of design variables of RDG and ES are analyzed for the joint optimal allocation. The paper proposes a probabilistic generation model for solar DG and wind DG. This generation model and IEEE-RTS based load model are integrated into an optimal power flow along with energy storage. The non-linear constrained optimization problem is solved by robust and high-performance metaheuristic, symbiotic organisms search (SOS) optimization. Case studies are performed on a typical 34 - bus test system using MATLAB®