N. Gupta, Griffin D. Francis, Juan Ospina, Alvi Newaz, E. Collins, O. Faruque, R. Meeker, Mario Harper
{"title":"具有太阳能和储能的微电网成本最优控制","authors":"N. Gupta, Griffin D. Francis, Juan Ospina, Alvi Newaz, E. Collins, O. Faruque, R. Meeker, Mario Harper","doi":"10.1109/TDC.2018.8440304","DOIUrl":null,"url":null,"abstract":"Solar power availability is intermittent and must be accompanied by an energy storage system (ESS) so that the effect of variability can be minimized. Hence, a strategy is needed to find the optimum combination of grid power, solar power, and power from the ESS so that the total cost of energy can be minimized. A solution to this problem is proposed here as Advanced Optimal Resource Allocation (AORA). This control scheme uses the prediction of Photovoltaic (PV) power availability, the real-time price of energy, and the levelized cost of energy for both PV and ESS to optimally combine the dispatch of power sources. Simulation results are presented for a 24 h prediction window and compared with a baseline power usage scheme that is based on a fixed charging and discharging schedule for the ESS. The comparison shows that AORA results in a substantial cost savings over the baseline scheme.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"19 1","pages":"1-9"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Cost Optimal Control of Microgrids Having Solar Power and Energy Storage\",\"authors\":\"N. Gupta, Griffin D. Francis, Juan Ospina, Alvi Newaz, E. Collins, O. Faruque, R. Meeker, Mario Harper\",\"doi\":\"10.1109/TDC.2018.8440304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Solar power availability is intermittent and must be accompanied by an energy storage system (ESS) so that the effect of variability can be minimized. Hence, a strategy is needed to find the optimum combination of grid power, solar power, and power from the ESS so that the total cost of energy can be minimized. A solution to this problem is proposed here as Advanced Optimal Resource Allocation (AORA). This control scheme uses the prediction of Photovoltaic (PV) power availability, the real-time price of energy, and the levelized cost of energy for both PV and ESS to optimally combine the dispatch of power sources. Simulation results are presented for a 24 h prediction window and compared with a baseline power usage scheme that is based on a fixed charging and discharging schedule for the ESS. The comparison shows that AORA results in a substantial cost savings over the baseline scheme.\",\"PeriodicalId\":6568,\"journal\":{\"name\":\"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)\",\"volume\":\"19 1\",\"pages\":\"1-9\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TDC.2018.8440304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDC.2018.8440304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cost Optimal Control of Microgrids Having Solar Power and Energy Storage
Solar power availability is intermittent and must be accompanied by an energy storage system (ESS) so that the effect of variability can be minimized. Hence, a strategy is needed to find the optimum combination of grid power, solar power, and power from the ESS so that the total cost of energy can be minimized. A solution to this problem is proposed here as Advanced Optimal Resource Allocation (AORA). This control scheme uses the prediction of Photovoltaic (PV) power availability, the real-time price of energy, and the levelized cost of energy for both PV and ESS to optimally combine the dispatch of power sources. Simulation results are presented for a 24 h prediction window and compared with a baseline power usage scheme that is based on a fixed charging and discharging schedule for the ESS. The comparison shows that AORA results in a substantial cost savings over the baseline scheme.