{"title":"考虑最优日调度的混合整数粒子群优化双层规划模型","authors":"Korawitch Kaiyawong, Chakit Plongkrathoke, Keerati Chayakulkheeree","doi":"10.4186/ej.2023.27.8.13","DOIUrl":null,"url":null,"abstract":". This paper proposes a bi-level optimization (BLO) approach for optimal battery energy storage system (BESS) allocation (OBA) in distribution network (DN) considering optimal BESS daily scheduling (OBDS). The objective is to obtain the best locations and daily scheduling of BESSs that minimize total energy loss in DNs. In the upper-level of the proposed BLO method, the OBA is solved by mixed-integer particle swarm optimization (MIPSO). Meanwhile, the OBDS is solved as a sub-problem by particle swarm optimization in the lower-level of BLO. The proposed BLO based OBA considering OBDS algorithm had been tested with IEEE 33-bus radial distribution test system using load profile of Thai’s power system during summer, winter, and rainy seasons comparing to mixed-integer genetic algorithm (MIGA) method. The simulation result showed that the proposed lower-level OBDS can efficiently minimize the total daily loss by BESS scheduling. Moreover, the proposed algorithm can also achieve the optimal placement of BESS.","PeriodicalId":11618,"journal":{"name":"Engineering Journal","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bi-level Planning Model for Optimal Battery Energy Storage Allocation Considering Optimal Daily Scheduling Using Mixed-Integer Particle Swarm Optimization\",\"authors\":\"Korawitch Kaiyawong, Chakit Plongkrathoke, Keerati Chayakulkheeree\",\"doi\":\"10.4186/ej.2023.27.8.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". This paper proposes a bi-level optimization (BLO) approach for optimal battery energy storage system (BESS) allocation (OBA) in distribution network (DN) considering optimal BESS daily scheduling (OBDS). The objective is to obtain the best locations and daily scheduling of BESSs that minimize total energy loss in DNs. In the upper-level of the proposed BLO method, the OBA is solved by mixed-integer particle swarm optimization (MIPSO). Meanwhile, the OBDS is solved as a sub-problem by particle swarm optimization in the lower-level of BLO. The proposed BLO based OBA considering OBDS algorithm had been tested with IEEE 33-bus radial distribution test system using load profile of Thai’s power system during summer, winter, and rainy seasons comparing to mixed-integer genetic algorithm (MIGA) method. The simulation result showed that the proposed lower-level OBDS can efficiently minimize the total daily loss by BESS scheduling. Moreover, the proposed algorithm can also achieve the optimal placement of BESS.\",\"PeriodicalId\":11618,\"journal\":{\"name\":\"Engineering Journal\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4186/ej.2023.27.8.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4186/ej.2023.27.8.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bi-level Planning Model for Optimal Battery Energy Storage Allocation Considering Optimal Daily Scheduling Using Mixed-Integer Particle Swarm Optimization
. This paper proposes a bi-level optimization (BLO) approach for optimal battery energy storage system (BESS) allocation (OBA) in distribution network (DN) considering optimal BESS daily scheduling (OBDS). The objective is to obtain the best locations and daily scheduling of BESSs that minimize total energy loss in DNs. In the upper-level of the proposed BLO method, the OBA is solved by mixed-integer particle swarm optimization (MIPSO). Meanwhile, the OBDS is solved as a sub-problem by particle swarm optimization in the lower-level of BLO. The proposed BLO based OBA considering OBDS algorithm had been tested with IEEE 33-bus radial distribution test system using load profile of Thai’s power system during summer, winter, and rainy seasons comparing to mixed-integer genetic algorithm (MIGA) method. The simulation result showed that the proposed lower-level OBDS can efficiently minimize the total daily loss by BESS scheduling. Moreover, the proposed algorithm can also achieve the optimal placement of BESS.