Venkata Ramakrishna Padullaparthi, V. Sarangan, A. Sivasubramaniam
{"title":"sUncover: Estimating the Hidden Behind-the-meter Solar Rooftop and Battery Capacities in Grids","authors":"Venkata Ramakrishna Padullaparthi, V. Sarangan, A. Sivasubramaniam","doi":"10.1109/ISGT.2019.8791573","DOIUrl":null,"url":null,"abstract":"As the technology costs of solar rooftops decline, small scale rooftops continue to become viable and grow without formal subsidies from the utility companies. Many new installations will continue to exist behind-the-meter (remain invisible), which poses challenges to the operating utilities for infrastructure and operations planning. This paper presents an approach to estimate the behind-the-meter solar PV size and the battery capacities. The proposed approach is based on energy balancing in buildings, and relies on data that is commonly available with utilities. The proposed approach is validated using a real-world dataset of 716 residential customers from a developed economy. The approach is compared with two baselines used by the studied Utility company. Results from the case study show that in 85% of the cases, the proposed approach has an accuracy of 98% in estimating the rooftop PV capacity (accuracies of baselines were in range 0%-30%). In estimating the battery capacity, the approach's estimates had less than 20% error in 70% of the cases (versus 35% error for baselines). The approach is also capable of discovering battery (dis)charging schedules, which is an additional useful information for utilities.","PeriodicalId":182098,"journal":{"name":"2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT.2019.8791573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
As the technology costs of solar rooftops decline, small scale rooftops continue to become viable and grow without formal subsidies from the utility companies. Many new installations will continue to exist behind-the-meter (remain invisible), which poses challenges to the operating utilities for infrastructure and operations planning. This paper presents an approach to estimate the behind-the-meter solar PV size and the battery capacities. The proposed approach is based on energy balancing in buildings, and relies on data that is commonly available with utilities. The proposed approach is validated using a real-world dataset of 716 residential customers from a developed economy. The approach is compared with two baselines used by the studied Utility company. Results from the case study show that in 85% of the cases, the proposed approach has an accuracy of 98% in estimating the rooftop PV capacity (accuracies of baselines were in range 0%-30%). In estimating the battery capacity, the approach's estimates had less than 20% error in 70% of the cases (versus 35% error for baselines). The approach is also capable of discovering battery (dis)charging schedules, which is an additional useful information for utilities.