{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T01:02:23Z","timestamp":1769821343921,"version":"3.49.0"},"reference-count":13,"publisher":"Springer Science and Business Media LLC","issue":"S1","license":[{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T00:00:00Z","timestamp":1603843200000},"content-version":"vor","delay-in-days":27,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Energy Inform"],"published-print":{"date-parts":[[2020,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n<jats:p>In the context of a pilot project, the Lugaggia Innovation Community (LIC), we address the problem of non-intrusive load monitoring for the purpose of demand side management on low voltage grids in presence of distributed power generation (photovoltaic). From the power readings of smart meters, we estimate the photovoltaic production and detect the activation of major loads (heatpumps and domestic water heaters). Experiments, conducted with real data and in silico, show that exploiting meter readings only, we can estimate PV production with MAPE ranging from 4.6% (best case) to 41.9% (worst case). Even with non negligible photovoltaic production estimation errors, the proposed method is capable of detecting the activation of heatpumps and domestic water heaters.<\/jats:p>","DOI":"10.1186\/s42162-020-00128-2","type":"journal-article","created":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T13:03:06Z","timestamp":1603890186000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Non intrusive load monitoring for demand side management"],"prefix":"10.1186","volume":"3","author":[{"given":"Matteo","family":"Salani","sequence":"first","affiliation":[]},{"given":"Marco","family":"Derboni","sequence":"additional","affiliation":[]},{"given":"Davide","family":"Rivola","sequence":"additional","affiliation":[]},{"given":"Vasco","family":"Medici","sequence":"additional","affiliation":[]},{"given":"Lorenzo","family":"Nespoli","sequence":"additional","affiliation":[]},{"given":"Federico","family":"Rosato","sequence":"additional","affiliation":[]},{"given":"Andrea E.","family":"Rizzoli","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,28]]},"reference":[{"issue":"4","key":"128_CR1","doi-asserted-by":"publisher","first-page":"3133","DOI":"10.1109\/TPWRS.2020.2966732","volume":"35","author":"F Bu","year":"2020","unstructured":"Bu, F, Dehghanpour K, Yuan Y, Wang Z, Zhang Y (2020) A data-driven game-theoretic approach for behind-the-meter pv generation disaggregation. IEEE Trans Power Syst 35(4):3133\u20133144.","journal-title":"IEEE Trans Power Syst"},{"issue":"2017","key":"128_CR2","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1016\/j.apenergy.2016.10.040","volume":"185","author":"A Cominola","year":"2017","unstructured":"Cominola, A, Giuliani M, Piga D, Castelletti A, Rizzoli AE (2017) A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring. Applied Energy 185(2017):331\u2013344.","journal-title":"Applied Energy"},{"issue":"12","key":"128_CR3","doi-asserted-by":"publisher","first-page":"1870","DOI":"10.1109\/5.192069","volume":"80","author":"GW Hart","year":"1992","unstructured":"Hart, GW (1992) Non-intrusive appliance load monitoring. Proc IEEE 80(12):1870\u20131891.","journal-title":"Proc IEEE"},{"issue":"29","key":"128_CR4","doi-asserted-by":"publisher","first-page":"884","DOI":"10.21105\/joss.00884","volume":"3","author":"WF Holmgren","year":"2018","unstructured":"Holmgren, WF, Hansen CW, Mikofski MA (2018) pvlib python: a python package for modeling solar energy systems. J Open Source Softw 3(29):884.","journal-title":"J Open Source Softw"},{"issue":"1","key":"128_CR5","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1109\/TSG.2017.2753802","volume":"10","author":"W Kong","year":"2019","unstructured":"Kong, W, Dong ZY, Jia Y, Hill DJ, Xu Y, Zhang Y (2019) Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network. IEEE Trans Smart Grid 10(1):841\u2013851.","journal-title":"IEEE Trans Smart Grid"},{"key":"128_CR6","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1016\/j.solener.2017.10.039","volume":"158","author":"L Nespoli","year":"2017","unstructured":"Nespoli, L, Medici V (2017) An unsupervised method for estimating the global horizontal irradiance from photovoltaic power measurements. Sol Energy 158:701\u2013710.","journal-title":"Sol Energy"},{"issue":"3","key":"128_CR7","doi-asserted-by":"publisher","first-page":"1044","DOI":"10.1109\/TCST.2015.2476777","volume":"24","author":"D Piga","year":"2016","unstructured":"Piga, D, Cominola A, Giuliani M, Castelletti A, Rizzoli AE (2016) Sparse Optimization for Automated Energy End Use Disaggregation. IEEE Trans Cont Sys Tech 24(3):1044\u20131051.","journal-title":"IEEE Trans Cont Sys Tech"},{"key":"128_CR8","unstructured":"Rosato, F, Medici V, Rudel R (2018) Krangpower: a Smart Grid Simulation Package. \nhttps:\/\/krangpower.readthedocs.io\n\n. Accessed 4 Oct 2020."},{"issue":"S1","key":"128_CR9","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1186\/s42162-019-0089-8","volume":"2","author":"C Rottondi","year":"2019","unstructured":"Rottondi, C, Derboni M, Piga D, Rizzoli AE (2019) An optimisation-based energy disaggregation algorithm for low frequency smart meter data. Energy Inform 2(S1):13.","journal-title":"Energy Inform"},{"issue":"9","key":"128_CR10","doi-asserted-by":"publisher","first-page":"2148","DOI":"10.3390\/en13092148","volume":"13","author":"PA Schirmer","year":"2020","unstructured":"Schirmer, PA, Mporas I, Sheikh-Akbari A (2020) Energy Disaggregation Using Two-Stage Fusion of Binary Device Detectors. Energies 13(9):2148.","journal-title":"Energies"},{"issue":"9","key":"128_CR11","doi-asserted-by":"publisher","first-page":"3904","DOI":"10.1109\/TII.2018.2791932","volume":"14","author":"F Sossan","year":"2018","unstructured":"Sossan, F, Nespoli L, Medici V, Paolone M (2018) Unsupervised disaggregation of photovoltaic production from composite power flow measurements of heterogeneous prosumers. IEEE Trans Ind Inform 14(9):3904\u20133913.","journal-title":"IEEE Trans Ind Inform"},{"issue":"1","key":"128_CR12","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/TCE.2011.5735484","volume":"57","author":"M Zeifman","year":"2011","unstructured":"Zeifman, M, Roth K (2011) Nonintrusive Appliance Load Monitoring: Review and Outlook. IEEE Trans Consum Electron 57(1):76\u201384.","journal-title":"IEEE Trans Consum Electron"},{"issue":"12","key":"128_CR13","doi-asserted-by":"publisher","first-page":"16838","DOI":"10.3390\/s121216838","volume":"12","author":"A Zoha","year":"2012","unstructured":"Zoha, A, Gluhak A, Imran M, Rajasegarar S (2012) Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey. Sensors 12(12):16838\u201316866.","journal-title":"Sensors"}],"container-title":["Energy Informatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s42162-020-00128-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s42162-020-00128-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s42162-020-00128-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T13:34:45Z","timestamp":1603892085000},"score":1,"resource":{"primary":{"URL":"https:\/\/energyinformatics.springeropen.com\/articles\/10.1186\/s42162-020-00128-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10]]},"references-count":13,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2020,10]]}},"alternative-id":["128"],"URL":"https:\/\/doi.org\/10.1186\/s42162-020-00128-2","relation":{},"ISSN":["2520-8942"],"issn-type":[{"value":"2520-8942","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10]]},"assertion":[{"value":"28 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"25"}}