{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:19:48Z","timestamp":1750220388012,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,6,22]],"date-time":"2021-06-22T00:00:00Z","timestamp":1624320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100010785","name":"Canada First Research Excellence Fund","doi-asserted-by":"publisher","award":["FES T06-P07"],"award-info":[{"award-number":["FES T06-P07"]}],"id":[{"id":"10.13039\/501100010785","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,6,22]]},"DOI":"10.1145\/3447555.3464856","type":"proceedings-article","created":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T04:49:35Z","timestamp":1624423775000},"page":"225-230","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Disaggregating Solar Generation Using Smart Meter Data and Proxy Measurements from Neighbouring Sites"],"prefix":"10.1145","author":[{"given":"Xinlei","family":"Chen","sequence":"first","affiliation":[{"name":"University of Alberta, Edmonton, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moosa Moghimi","family":"Haji","sequence":"additional","affiliation":[{"name":"University of Alberta, Edmonton, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Omid","family":"Ardakanian","sequence":"additional","affiliation":[{"name":"University of Alberta, Edmonton, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,6,22]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Ausgrid. [n.d.]. Solar home electricity data. https:\/\/www.ausgrid.com.au\/Industry\/Our-Research\/Data-to-share\/Solar-home-electricity-data.  Ausgrid. [n.d.]. Solar home electricity data. https:\/\/www.ausgrid.com.au\/Industry\/Our-Research\/Data-to-share\/Solar-home-electricity-data."},{"volume-title":"Proc. 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 456--466","author":"Noman","key":"e_1_3_2_1_2_1","unstructured":"Noman Bashir et al. 2019. Solar-TK: A Data-Driven Toolkit for Solar PV Performance Modeling and Forecasting . In Proc. 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 456--466 . Noman Bashir et al. 2019. Solar-TK: A Data-Driven Toolkit for Solar PV Performance Modeling and Forecasting. In Proc. 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). IEEE, 456--466."},{"volume-title":"Proc. 6th International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. ACM, 193--202","author":"Nipun","key":"e_1_3_2_1_3_1","unstructured":"Nipun Batra et al. 2019. Towards Reproducible State-of-the-Art Energy Disaggregation . In Proc. 6th International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. ACM, 193--202 . Nipun Batra et al. 2019. Towards Reproducible State-of-the-Art Energy Disaggregation. In Proc. 6th International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. ACM, 193--202."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2020.2966732"},{"key":"e_1_3_2_1_5_1","volume-title":"Proc. 8th International Conference on Future Energy Systems","author":"Dong","year":"2017","unstructured":"Dong Chen et al. 2017. SunDance: Black-box Behind-the-Meter Solar Disaggregation . Proc. 8th International Conference on Future Energy Systems ( 2017 ), 45--55. Dong Chen et al. 2017. SunDance: Black-box Behind-the-Meter Solar Disaggregation. Proc. 8th International Conference on Future Energy Systems (2017), 45--55."},{"volume-title":"Proc. 5th International Workshop on Non-Intrusive Load Monitoring. ACM, 6--10","author":"Xinlei","key":"e_1_3_2_1_6_1","unstructured":"Xinlei Chen et al. 2020. Solar Disaggregation: State of the Art and Open Challenges . In Proc. 5th International Workshop on Non-Intrusive Load Monitoring. ACM, 6--10 . Xinlei Chen et al. 2020. Solar Disaggregation: State of the Art and Open Challenges. In Proc. 5th International Workshop on Non-Intrusive Load Monitoring. ACM, 6--10."},{"volume-title":"International Conference on Communications, Control, and Computing Technologies for Smart Grids. IEEE, 1--6.","author":"Chung M.","key":"e_1_3_2_1_7_1","unstructured":"Chung M. Cheung et al. 2018. Behind-the-Meter Solar Generation Disaggregation using Consumer Mixture Models . In International Conference on Communications, Control, and Computing Technologies for Smart Grids. IEEE, 1--6. Chung M. Cheung et al. 2018. Behind-the-Meter Solar Generation Disaggregation using Consumer Mixture Models. In International Conference on Communications, Control, and Computing Technologies for Smart Grids. IEEE, 1--6."},{"volume-title":"Proc. 11th International Conference on Future Energy Systems. ACM, 308--313","author":"Julian","key":"e_1_3_2_1_8_1","unstructured":"Julian de Hoog et al. 2020. Using Satellite and Aerial Imagery for Identification of Solar PV: State of the Art and Research Opportunities . In Proc. 11th International Conference on Future Energy Systems. ACM, 308--313 . Julian de Hoog et al. 2020. Using Satellite and Aerial Imagery for Identification of Solar PV: State of the Art and Research Opportunities. In Proc. 11th International Conference on Future Energy Systems. ACM, 308--313."},{"key":"e_1_3_2_1_10_1","volume-title":"Global Energy Review","author":"International Energy Agency","year":"2020","unstructured":"International Energy Agency . 2020. Global Energy Review 2020 . https:\/\/www.iea.org\/reports\/global-energy-review-2020. Accessed 01.02.2021. International Energy Agency. 2020. Global Energy Review 2020. https:\/\/www.iea.org\/reports\/global-energy-review-2020. Accessed 01.02.2021."},{"volume-title":"IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids. 1--6.","author":"Farzana","key":"e_1_3_2_1_11_1","unstructured":"Farzana Kabir et al. 2019. Estimation of Behind-the-Meter Solar Generation by Integrating Physical with Statistical Models . In IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids. 1--6. Farzana Kabir et al. 2019. Estimation of Behind-the-Meter Solar Generation by Integrating Physical with Statistical Models. In IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids. 1--6."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.segan.2017.11.001"},{"key":"e_1_3_2_1_13_1","first-page":"747","article-title":"Unsupervised Disaggregation of Low Frequency Power Measurements","volume":"11","author":"Hyungsul Kim","year":"2011","unstructured":"Hyungsul Kim et al. 2011 . Unsupervised Disaggregation of Low Frequency Power Measurements . Proc. SIAM Conference on Data Mining 11 , 747 -- 758 . Hyungsul Kim et al. 2011. Unsupervised Disaggregation of Low Frequency Power Measurements. Proc. SIAM Conference on Data Mining 11, 747--758.","journal-title":"Proc. SIAM Conference on Data Mining"},{"key":"e_1_3_2_1_14_1","unstructured":"Pecan Street Inc. [n.d.]. Dataport. https:\/\/www.pecanstreet.org\/dataport\/.  Pecan Street Inc. [n.d.]. Dataport. https:\/\/www.pecanstreet.org\/dataport\/."},{"key":"e_1_3_2_1_15_1","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","author":"Fabian Pedregosa","year":"2011","unstructured":"Fabian Pedregosa et al. 2011 . Scikit-learn: Machine learning in Python . Journal of Machine Learning Research 12 , Oct (2011), 2825 -- 2830 . Fabian Pedregosa et al. 2011. Scikit-learn: Machine learning in Python. Journal of Machine Learning Research 12, Oct (2011), 2825--2830.","journal-title":"Journal of Machine Learning Research 12"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2015.2502140"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2016.2533164"},{"key":"e_1_3_2_1_18_1","unstructured":"Solcast. [n.d.]. Weather Dataset. https:\/\/toolkit.solcast.com.au\/.  Solcast. [n.d.]. Weather Dataset. https:\/\/toolkit.solcast.com.au\/."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2791932"},{"key":"e_1_3_2_1_20_1","volume-title":"38th Photovoltaic Specialists Conference. IEEE, 003048--003052","author":"Joshua Stein","year":"2012","unstructured":"Joshua Stein . 2012 . The Photovoltaic Performance Modeling Collaborative (PVPMC) . In 38th Photovoltaic Specialists Conference. IEEE, 003048--003052 . Joshua Stein. 2012. The Photovoltaic Performance Modeling Collaborative (PVPMC). In 38th Photovoltaic Specialists Conference. IEEE, 003048--003052."},{"volume-title":"Proc. 5th Conference on Systems for Built Environments. ACM, 43--52","author":"Michaelangelo","key":"e_1_3_2_1_21_1","unstructured":"Michaelangelo Tabone et al. 2018. Disaggregating Solar Generation behind Individual Meters in Real Time . In Proc. 5th Conference on Systems for Built Environments. ACM, 43--52 . Michaelangelo Tabone et al. 2018. Disaggregating Solar Generation behind Individual Meters in Real Time. In Proc. 5th Conference on Systems for Built Environments. ACM, 43--52."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Chaoyun Zhang et al. 2018. Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring. In AAAI.  Chaoyun Zhang et al. 2018. Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring. In AAAI.","DOI":"10.1609\/aaai.v32i1.11873"}],"event":{"name":"e-Energy '21: The Twelfth ACM International Conference on Future Energy Systems","acronym":"e-Energy '21","location":"Virtual Event Italy"},"container-title":["Proceedings of the Twelfth ACM International Conference on Future Energy Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447555.3464856","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447555.3464856","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:32Z","timestamp":1750191512000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447555.3464856"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,22]]},"references-count":21,"alternative-id":["10.1145\/3447555.3464856","10.1145\/3447555"],"URL":"https:\/\/doi.org\/10.1145\/3447555.3464856","relation":{},"subject":[],"published":{"date-parts":[[2021,6,22]]},"assertion":[{"value":"2021-06-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}