{"title":"基于遗传算法的产消一体化PV-BESS系统定径方法","authors":"S. Korjani, A. Serpi, A. Damiano","doi":"10.1109/IESES45645.2020.9210700","DOIUrl":null,"url":null,"abstract":"A procedure for properly sizing integrated configurations of photovoltaic (PV) and battery energy storage systems (BESSs) is presented in this paper. Specifically, an energy management strategy oriented to maximise the electricity self-consumption has been used. In this regard, the energy management of Li-ion BESS is optimised by means of a specific tool based on a Genetic Algorithm (GA). In order to determine the best rated power and capacity of integrated PV-BESS system for residential and commercial users, the optimisation has been performed for different combination of PV and BESS rated powers and capacities, evaluating, for each of them, the annual self-consumption. The analysis of the results permits the proper choice of the PV-BESS system for a specific prosumer end for a given self-consumption target. Moreover, the proposed design approach highlights that the increase of BESS size for a defined electricity demand may lead to weak benefits in terms of increased self-consumption and, thus, to an unsuitable oversizing of the PV-BESS system.","PeriodicalId":262855,"journal":{"name":"2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"A Genetic Algorithm Approach for Sizing Integrated PV-BESS Systems for Prosumers\",\"authors\":\"S. Korjani, A. Serpi, A. Damiano\",\"doi\":\"10.1109/IESES45645.2020.9210700\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A procedure for properly sizing integrated configurations of photovoltaic (PV) and battery energy storage systems (BESSs) is presented in this paper. Specifically, an energy management strategy oriented to maximise the electricity self-consumption has been used. In this regard, the energy management of Li-ion BESS is optimised by means of a specific tool based on a Genetic Algorithm (GA). In order to determine the best rated power and capacity of integrated PV-BESS system for residential and commercial users, the optimisation has been performed for different combination of PV and BESS rated powers and capacities, evaluating, for each of them, the annual self-consumption. The analysis of the results permits the proper choice of the PV-BESS system for a specific prosumer end for a given self-consumption target. Moreover, the proposed design approach highlights that the increase of BESS size for a defined electricity demand may lead to weak benefits in terms of increased self-consumption and, thus, to an unsuitable oversizing of the PV-BESS system.\",\"PeriodicalId\":262855,\"journal\":{\"name\":\"2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IESES45645.2020.9210700\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IESES45645.2020.9210700","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Genetic Algorithm Approach for Sizing Integrated PV-BESS Systems for Prosumers
A procedure for properly sizing integrated configurations of photovoltaic (PV) and battery energy storage systems (BESSs) is presented in this paper. Specifically, an energy management strategy oriented to maximise the electricity self-consumption has been used. In this regard, the energy management of Li-ion BESS is optimised by means of a specific tool based on a Genetic Algorithm (GA). In order to determine the best rated power and capacity of integrated PV-BESS system for residential and commercial users, the optimisation has been performed for different combination of PV and BESS rated powers and capacities, evaluating, for each of them, the annual self-consumption. The analysis of the results permits the proper choice of the PV-BESS system for a specific prosumer end for a given self-consumption target. Moreover, the proposed design approach highlights that the increase of BESS size for a defined electricity demand may lead to weak benefits in terms of increased self-consumption and, thus, to an unsuitable oversizing of the PV-BESS system.