{"title":"包含充电站和可再生能源的微电网优化规划","authors":"A. Eid, M. Ibrahim, S. Kamel","doi":"10.1109/MEPCON50283.2021.9686196","DOIUrl":null,"url":null,"abstract":"Electric vehicles are an important way to reduce greenhouse gas emissions. The impact of ozone pollutants and support for large-scale renewables are reduced by electric vehicles and the dependence on fossil fuels. As a decarbonizer tool and an auxiliary service provider, charging-discharging coordination between electric vehicles and the power grid is essential. This paper analyzes and optimizes a microgrid equipped with an Electric Vehicles charging station (EVCS) and distributed generation (DG) with a minimum loss objective. The assumed capacity of the station is 900 EVCSs of 12 kWh each. Electric Vehicles (EVs) enter the charging station at a random state of charge where they are charged under constant power mode. The EVs are connected until they are fully charged and then disconnected. The fleet of EVs enters the station every four hours throughout the day. The 33-bus radial distribution system is taken as a test system representing the microgrid with demand uncertainty. A renewable source is optimally allocated into the microgrid to minimize the total power loss using the newly published Hunger Games Search (HGS) optimization algorithm. The optimized DG operates in two case studies of unity power factor (UPF) and optimal power factor (OPF). The obtained results during the 24-hr operation of the system emphasize the efficient methodology of the proposed planning of the microgrid and the competent capability of the HGS algorithm to minimize the power loss of the microgrid and other performance parameters. Moreover, the operation of the DG with OPF achieves better outcomes than that with UPF during the complete 24-hr demand.","PeriodicalId":141478,"journal":{"name":"2021 22nd International Middle East Power Systems Conference (MEPCON)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimal Planning of Microgrids Including Charging Stations and Renewable Energy Sources\",\"authors\":\"A. Eid, M. Ibrahim, S. Kamel\",\"doi\":\"10.1109/MEPCON50283.2021.9686196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electric vehicles are an important way to reduce greenhouse gas emissions. The impact of ozone pollutants and support for large-scale renewables are reduced by electric vehicles and the dependence on fossil fuels. As a decarbonizer tool and an auxiliary service provider, charging-discharging coordination between electric vehicles and the power grid is essential. This paper analyzes and optimizes a microgrid equipped with an Electric Vehicles charging station (EVCS) and distributed generation (DG) with a minimum loss objective. The assumed capacity of the station is 900 EVCSs of 12 kWh each. Electric Vehicles (EVs) enter the charging station at a random state of charge where they are charged under constant power mode. The EVs are connected until they are fully charged and then disconnected. The fleet of EVs enters the station every four hours throughout the day. The 33-bus radial distribution system is taken as a test system representing the microgrid with demand uncertainty. A renewable source is optimally allocated into the microgrid to minimize the total power loss using the newly published Hunger Games Search (HGS) optimization algorithm. The optimized DG operates in two case studies of unity power factor (UPF) and optimal power factor (OPF). The obtained results during the 24-hr operation of the system emphasize the efficient methodology of the proposed planning of the microgrid and the competent capability of the HGS algorithm to minimize the power loss of the microgrid and other performance parameters. Moreover, the operation of the DG with OPF achieves better outcomes than that with UPF during the complete 24-hr demand.\",\"PeriodicalId\":141478,\"journal\":{\"name\":\"2021 22nd International Middle East Power Systems Conference (MEPCON)\",\"volume\":\"110 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 22nd International Middle East Power Systems Conference (MEPCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MEPCON50283.2021.9686196\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 22nd International Middle East Power Systems Conference (MEPCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEPCON50283.2021.9686196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Planning of Microgrids Including Charging Stations and Renewable Energy Sources
Electric vehicles are an important way to reduce greenhouse gas emissions. The impact of ozone pollutants and support for large-scale renewables are reduced by electric vehicles and the dependence on fossil fuels. As a decarbonizer tool and an auxiliary service provider, charging-discharging coordination between electric vehicles and the power grid is essential. This paper analyzes and optimizes a microgrid equipped with an Electric Vehicles charging station (EVCS) and distributed generation (DG) with a minimum loss objective. The assumed capacity of the station is 900 EVCSs of 12 kWh each. Electric Vehicles (EVs) enter the charging station at a random state of charge where they are charged under constant power mode. The EVs are connected until they are fully charged and then disconnected. The fleet of EVs enters the station every four hours throughout the day. The 33-bus radial distribution system is taken as a test system representing the microgrid with demand uncertainty. A renewable source is optimally allocated into the microgrid to minimize the total power loss using the newly published Hunger Games Search (HGS) optimization algorithm. The optimized DG operates in two case studies of unity power factor (UPF) and optimal power factor (OPF). The obtained results during the 24-hr operation of the system emphasize the efficient methodology of the proposed planning of the microgrid and the competent capability of the HGS algorithm to minimize the power loss of the microgrid and other performance parameters. Moreover, the operation of the DG with OPF achieves better outcomes than that with UPF during the complete 24-hr demand.