{"title":"Disaggregating solar generation behind individual meters in real time","authors":"Michaelangelo D. Tabone, S. Kiliccote, E. Kara","doi":"10.1145/3276774.3276776","DOIUrl":null,"url":null,"abstract":"Real-time photovoltaic (PV) generation information is crucial for distribution system operations such as switching, state-estimation, and voltage management. However, most behind-the-meter solar installations are not monitored. Typically, the only information available to the distribution system operator is the installed capacity of solar behind each meter; though in some cases even the presence of solar may be unknown. We present a method for disaggreagating behind-the-meter solar generation using only information that is already available in most distribution systems: advanced metering infrastructure, substation monitoring, and generation monitoring at a few PV systems nearby the circuit. The proposed method accurately predicts which homes have solar in over 90% of cases, and recovers the 15-min resolution PV generation signals with root mean square errors between 20% and 50% of average daily PV generation both historically and real-time. A sensitivity analysis shows the method to be robust to the number of buildings and time span of data used to fit. However including more than 3 solar proxies can cause false positive of PV systems behind meters. We find that the proposed method performs better at homes that export electricity to the grid more often.","PeriodicalId":294697,"journal":{"name":"Proceedings of the 5th Conference on Systems for Built Environments","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th Conference on Systems for Built Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3276774.3276776","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 33
Abstract
Real-time photovoltaic (PV) generation information is crucial for distribution system operations such as switching, state-estimation, and voltage management. However, most behind-the-meter solar installations are not monitored. Typically, the only information available to the distribution system operator is the installed capacity of solar behind each meter; though in some cases even the presence of solar may be unknown. We present a method for disaggreagating behind-the-meter solar generation using only information that is already available in most distribution systems: advanced metering infrastructure, substation monitoring, and generation monitoring at a few PV systems nearby the circuit. The proposed method accurately predicts which homes have solar in over 90% of cases, and recovers the 15-min resolution PV generation signals with root mean square errors between 20% and 50% of average daily PV generation both historically and real-time. A sensitivity analysis shows the method to be robust to the number of buildings and time span of data used to fit. However including more than 3 solar proxies can cause false positive of PV systems behind meters. We find that the proposed method performs better at homes that export electricity to the grid more often.