{"id":"https://openalex.org/W3093800066","doi":"https://doi.org/10.3390/rs12203420","title":"Industry Experience of Developing Day-Ahead Photovoltaic Plant Forecasting System Based on Machine Learning","display_name":"Industry Experience of Developing Day-Ahead Photovoltaic Plant Forecasting System Based on Machine Learning","publication_year":2020,"publication_date":"2020-10-18","ids":{"openalex":"https://openalex.org/W3093800066","doi":"https://doi.org/10.3390/rs12203420","mag":"3093800066"},"language":"en","primary_location":{"id":"doi:10.3390/rs12203420","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12203420","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/rs12203420","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058514050","display_name":"Alexandra I. Khalyasmaa","orcid":"https://orcid.org/0000-0001-5327-6076"},"institutions":[{"id":"https://openalex.org/I130823665","display_name":"Ural Federal University","ror":"https://ror.org/00hs7dr46","country_code":"RU","type":"education","lineage":["https://openalex.org/I130823665"]},{"id":"https://openalex.org/I91727514","display_name":"Novosibirsk State Technical University","ror":"https://ror.org/01b2f6h61","country_code":"RU","type":"education","lineage":["https://openalex.org/I91727514"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Alexandra I. Khalyasmaa","raw_affiliation_strings":["Power Plants Department, Novosibirsk State Technical University, 630073 Novosibirsk, Russia","Ural Power Engineering Institute, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Ekaterinburg, Russia"],"raw_orcid":"https://orcid.org/0000-0001-5327-6076","affiliations":[{"raw_affiliation_string":"Power Plants Department, Novosibirsk State Technical University, 630073 Novosibirsk, Russia","institution_ids":["https://openalex.org/I91727514"]},{"raw_affiliation_string":"Ural Power Engineering Institute, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Ekaterinburg, Russia","institution_ids":["https://openalex.org/I130823665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045794533","display_name":"Stanislav A. Eroshenko","orcid":"https://orcid.org/0000-0001-9617-2154"},"institutions":[{"id":"https://openalex.org/I130823665","display_name":"Ural Federal University","ror":"https://ror.org/00hs7dr46","country_code":"RU","type":"education","lineage":["https://openalex.org/I130823665"]},{"id":"https://openalex.org/I91727514","display_name":"Novosibirsk State Technical University","ror":"https://ror.org/01b2f6h61","country_code":"RU","type":"education","lineage":["https://openalex.org/I91727514"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Stanislav A. Eroshenko","raw_affiliation_strings":["Power Plants Department, Novosibirsk State Technical University, 630073 Novosibirsk, Russia","Ural Power Engineering Institute, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Ekaterinburg, Russia"],"raw_orcid":"https://orcid.org/0000-0001-9617-2154","affiliations":[{"raw_affiliation_string":"Power Plants Department, Novosibirsk State Technical University, 630073 Novosibirsk, Russia","institution_ids":["https://openalex.org/I91727514"]},{"raw_affiliation_string":"Ural Power Engineering Institute, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Ekaterinburg, Russia","institution_ids":["https://openalex.org/I130823665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076693117","display_name":"Valeriy Tashchilin","orcid":"https://orcid.org/0000-0001-8763-3705"},"institutions":[{"id":"https://openalex.org/I130823665","display_name":"Ural Federal University","ror":"https://ror.org/00hs7dr46","country_code":"RU","type":"education","lineage":["https://openalex.org/I130823665"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Valeriy A. Tashchilin","raw_affiliation_strings":["Ural Power Engineering Institute, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Ekaterinburg, Russia"],"raw_orcid":"https://orcid.org/0000-0001-8763-3705","affiliations":[{"raw_affiliation_string":"Ural Power Engineering Institute, Ural Federal University named after the first President of Russia B.N. Yeltsin, 620002 Ekaterinburg, Russia","institution_ids":["https://openalex.org/I130823665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061354777","display_name":"R. Hariprakash","orcid":null},"institutions":[{"id":"https://openalex.org/I860813019","display_name":"Bharath University","ror":"https://ror.org/04yazpn06","country_code":"IN","type":"education","lineage":["https://openalex.org/I860813019"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hariprakash Ramachandran","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Bharath Institute of Higher Education and Research, Chennai 600073, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Bharath Institute of Higher Education and Research, Chennai 600073, India","institution_ids":["https://openalex.org/I860813019"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073199657","display_name":"T. Chakravarthi","orcid":"https://orcid.org/0000-0003-3955-1144"},"institutions":[{"id":"https://openalex.org/I860813019","display_name":"Bharath University","ror":"https://ror.org/04yazpn06","country_code":"IN","type":"education","lineage":["https://openalex.org/I860813019"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Teja Piepur Chakravarthi","raw_affiliation_strings":["Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai 600073, India"],"raw_orcid":"https://orcid.org/0000-0003-3955-1144","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai 600073, India","institution_ids":["https://openalex.org/I860813019"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075024454","display_name":"\u0414\u0435\u043d\u0438\u0441 \u0411\u0443\u0442\u0443\u0441\u043e\u0432","orcid":"https://orcid.org/0000-0002-8941-4220"},"institutions":[{"id":"https://openalex.org/I41518628","display_name":"Saint Petersburg State Electrotechnical University","ror":"https://ror.org/023bq8521","country_code":"RU","type":"education","lineage":["https://openalex.org/I41518628"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Denis N. Butusov","raw_affiliation_strings":["Youth Research Institute, Saint Petersburg Electrotechnical University \u201cLETI\u201d, 197376 Saint Petersburg, Russia","Youth Research Institute, Saint Petersburg Electrotechnical University \"LETI\", 197376 Saint Petersburg, Russia"],"raw_orcid":"https://orcid.org/0000-0002-8941-4220","affiliations":[{"raw_affiliation_string":"Youth Research Institute, Saint Petersburg Electrotechnical University \u201cLETI\u201d, 197376 Saint Petersburg, Russia","institution_ids":["https://openalex.org/I41518628"]},{"raw_affiliation_string":"Youth Research Institute, Saint Petersburg Electrotechnical University \"LETI\", 197376 Saint Petersburg, Russia","institution_ids":["https://openalex.org/I41518628"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075024454"],"corresponding_institution_ids":["https://openalex.org/I41518628"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":2.2788,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.90579009,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"12","issue":"20","first_page":"3420","last_page":"3420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10468","display_name":"Photovoltaic System Optimization Techniques","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/photovoltaic-system","display_name":"Photovoltaic system","score":0.7752957940101624},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6944022178649902},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6590083837509155},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5915460586547852},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5901904702186584},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5209751725196838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49244436621665955},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.46076512336730957},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.45061907172203064},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.42622458934783936},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.1688421070575714},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12212970852851868}],"concepts":[{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.7752957940101624},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6944022178649902},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6590083837509155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5915460586547852},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5901904702186584},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5209751725196838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49244436621665955},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.46076512336730957},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.45061907172203064},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.42622458934783936},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.1688421070575714},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12212970852851868},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/rs12203420","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12203420","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:elar.urfu.ru:10995/101382","is_oa":true,"landing_page_url":"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092891728&doi=10.3390%2frs12203420&partnerID=40&md5=b2c9b2b14e6a6b836ba26bd6cad8bab3","pdf_url":"https://www.mdpi.com/2072-4292/12/20/3420/pdf","source":{"id":"https://openalex.org/S4406922546","display_name":"Electronic Archive of Ural Federal University (ELAR UrFU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:caef643984eb420c95559e18984044c7","is_oa":true,"landing_page_url":"https://doaj.org/article/caef643984eb420c95559e18984044c7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 12, Iss 20, p 3420 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/20/3420/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12203420","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 12; Issue 20; Pages: 3420","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12203420","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12203420","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1120922828","https://openalex.org/W1508162533","https://openalex.org/W1516907816","https://openalex.org/W1986585426","https://openalex.org/W1989938710","https://openalex.org/W2007952998","https://openalex.org/W2047910093","https://openalex.org/W2059504782","https://openalex.org/W2063626689","https://openalex.org/W2107450528","https://openalex.org/W2126603600","https://openalex.org/W2158054309","https://openalex.org/W2158146421","https://openalex.org/W2162626239","https://openalex.org/W2292465733","https://openalex.org/W2327473694","https://openalex.org/W2343702657","https://openalex.org/W2564935578","https://openalex.org/W2604086375","https://openalex.org/W2607339923","https://openalex.org/W2608040492","https://openalex.org/W2762797296","https://openalex.org/W2763623424","https://openalex.org/W2765559313","https://openalex.org/W2801973365","https://openalex.org/W2884380318","https://openalex.org/W2888066844","https://openalex.org/W2889464331","https://openalex.org/W2890704507","https://openalex.org/W2895355360","https://openalex.org/W2902838464","https://openalex.org/W2911364384","https://openalex.org/W2949678421","https://openalex.org/W2955557342","https://openalex.org/W2963322289","https://openalex.org/W2963957027","https://openalex.org/W2972501022"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W4386690025","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W2885516856","https://openalex.org/W2073883415","https://openalex.org/W4289703016"],"abstract_inverted_index":{"This":[0],"article":[1,127],"highlights":[2],"the":[3,7,42,45,72,75,80,100,119,129,150,158,161,171,173,178,195,198,202],"industry":[4],"experience":[5],"of":[6,12,41,44,74,79,95,121,131,157,160,170,181,197,230],"development":[8],"and":[9,108,123,145,168,177,220],"practical":[10],"implementation":[11],"a":[13,24,32,89,93,112,155],"short-term":[14],"photovoltaic":[15,27,50,103,207],"forecasting":[16,54,81,209],"system":[17,35,76],"based":[18,56],"on":[19,57,111],"machine":[20,133],"learning":[21,134],"methods":[22],"for":[23,186,216,223],"real":[25],"industry-scale":[26],"power":[28,34,51,104],"plant":[29,105],"implemented":[30],"in":[31,64,77],"Russian":[33],"using":[36],"remote":[37],"data":[38],"acquisition.":[39],"One":[40],"goals":[43],"study":[46,199],"is":[47,62],"to":[48,70,149,204],"improve":[49,71],"plants":[52],"generation":[53],"accuracy":[55,213],"open-source":[58],"meteorological":[59],"data,":[60],"which":[61],"provided":[63],"regular":[65],"weather":[66],"forecasts.":[67],"In":[68],"order":[69],"robustness":[73],"terms":[78],"accuracy,":[82],"we":[83],"apply":[84],"newly":[85],"derived":[86],"feature":[87,96],"introduction,":[88],"factor":[90],"obtained":[91,152],"as":[92],"result":[94,156],"engineering":[97],"procedure,":[98],"characterizing":[99],"relationship":[101],"between":[102],"energy":[106,208],"production":[107],"solar":[109],"irradiation":[110],"horizontal":[113],"surface,":[114],"thus":[115],"taking":[116],"into":[117],"account":[118],"impacts":[120],"atmospheric":[122],"electrical":[124],"nature.":[125],"The":[126,190],"scrutinizes":[128],"application":[130,159,179],"different":[132,182,228],"algorithms,":[135,172],"including":[136],"Random":[137],"Forest":[138],"regressor,":[139],"Gradient":[140],"Boosting":[141],"Regressor,":[142],"Linear":[143],"Regression":[144],"Decision":[146],"Trees":[147],"regression,":[148],"remotely":[151],"data.":[153],"As":[154],"aforementioned":[162],"approaches":[163],"together":[164],"with":[165,211,227],"hyperparameters,":[166],"tuning":[167],"pipelining":[169],"optimal":[174],"structure,":[175],"parameters":[176],"sphere":[180],"regressors":[183],"were":[184],"identified":[185],"various":[187],"testing":[188],"samples.":[189],"mathematical":[191],"model":[192],"developed":[193],"within":[194],"framework":[196],"gave":[200],"us":[201],"opportunity":[203],"provide":[205],"robust":[206],"results":[210],"mean":[212],"over":[214,221],"92%":[215],"mostly-sunny":[217],"sample":[218],"days":[219,226],"83%":[222],"mostly":[224],"cloudy":[225],"types":[229],"precipitation.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2020-10-29T00:00:00"}