{"title":"电动汽车充电计划的成本和温室气体排放最小化","authors":"Rentao Wu, G. Tsagarakis, A. Collin, A. Kiprakis","doi":"10.1109/EVER.2017.7935877","DOIUrl":null,"url":null,"abstract":"This paper investigates the potential impact of a fleet of electric vehicles charging on the cost of electricity generation, greenhouse gas emissions (GHG) and power system demand through low voltage residential demand-side management (DSM). The proposed optimisation algorithm is used to shift electric vehicles charging loads to minimize the combined impact of three key parameters: financial, environmental, and demand variability. The results show that it is effective to reshape the power demand and reduce electricity cost and GHG emissions without affecting people's driving patterns.","PeriodicalId":395329,"journal":{"name":"2017 Twelfth International Conference on Ecological Vehicles and Renewable Energies (EVER)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"EV charging scheduling for cost and greenhouse gases emissions minimization\",\"authors\":\"Rentao Wu, G. Tsagarakis, A. Collin, A. Kiprakis\",\"doi\":\"10.1109/EVER.2017.7935877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the potential impact of a fleet of electric vehicles charging on the cost of electricity generation, greenhouse gas emissions (GHG) and power system demand through low voltage residential demand-side management (DSM). The proposed optimisation algorithm is used to shift electric vehicles charging loads to minimize the combined impact of three key parameters: financial, environmental, and demand variability. The results show that it is effective to reshape the power demand and reduce electricity cost and GHG emissions without affecting people's driving patterns.\",\"PeriodicalId\":395329,\"journal\":{\"name\":\"2017 Twelfth International Conference on Ecological Vehicles and Renewable Energies (EVER)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Twelfth International Conference on Ecological Vehicles and Renewable Energies (EVER)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EVER.2017.7935877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Twelfth International Conference on Ecological Vehicles and Renewable Energies (EVER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EVER.2017.7935877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
EV charging scheduling for cost and greenhouse gases emissions minimization
This paper investigates the potential impact of a fleet of electric vehicles charging on the cost of electricity generation, greenhouse gas emissions (GHG) and power system demand through low voltage residential demand-side management (DSM). The proposed optimisation algorithm is used to shift electric vehicles charging loads to minimize the combined impact of three key parameters: financial, environmental, and demand variability. The results show that it is effective to reshape the power demand and reduce electricity cost and GHG emissions without affecting people's driving patterns.