{"id":"https://openalex.org/W4408293813","doi":"https://doi.org/10.3390/sym17030414","title":"Photovoltaic Power Prediction Technology Based on Multi-Source Feature Fusion","display_name":"Photovoltaic Power Prediction Technology Based on Multi-Source Feature Fusion","publication_year":2025,"publication_date":"2025-03-10","ids":{"openalex":"https://openalex.org/W4408293813","doi":"https://doi.org/10.3390/sym17030414"},"language":"en","primary_location":{"id":"doi:10.3390/sym17030414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17030414","pdf_url":"https://www.mdpi.com/2073-8994/17/3/414/pdf?version=1741603305","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/17/3/414/pdf?version=1741603305","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101823589","display_name":"Xia Zhou","orcid":"https://orcid.org/0000-0003-0652-7156"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xia Zhou","raw_affiliation_strings":["Carbon Neutralization Advanced Technology Research Institute, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"],"affiliations":[{"raw_affiliation_string":"Carbon Neutralization Advanced Technology Research Institute, Nanjing University of Posts and Telecommunications, Nanjing 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027182317","display_name":"Xize Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xize Zhang","raw_affiliation_strings":["School of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077335074","display_name":"Jianfeng Dai","orcid":"https://orcid.org/0000-0002-1263-6191"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Dai","raw_affiliation_strings":["School of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030436726","display_name":"Tengfei Zhang","orcid":"https://orcid.org/0000-0002-2503-7024"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tengfei Zhang","raw_affiliation_strings":["School of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101823589"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":9.1379,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97197468,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"17","issue":"3","first_page":"414","last_page":"414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9988999962806702,"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":0.9988999962806702,"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/T10468","display_name":"Photovoltaic System Optimization Techniques","score":0.9897000193595886,"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"}},{"id":"https://openalex.org/T14444","display_name":"Power Systems and Renewable Energy","score":0.9772999882698059,"subfield":{"id":"https://openalex.org/subfields/2102","display_name":"Energy Engineering and Power Technology"},"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":0.7885270714759827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5929320454597473},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.520585834980011},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5015358924865723},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.48230600357055664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.426643967628479},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4035707712173462},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1901017129421234},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1452694535255432},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1015409529209137}],"concepts":[{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.7885270714759827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5929320454597473},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.520585834980011},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5015358924865723},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.48230600357055664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.426643967628479},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4035707712173462},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1901017129421234},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1452694535255432},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1015409529209137},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/sym17030414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17030414","pdf_url":"https://www.mdpi.com/2073-8994/17/3/414/pdf?version=1741603305","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/sym17030414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17030414","pdf_url":"https://www.mdpi.com/2073-8994/17/3/414/pdf?version=1741603305","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4408293813.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W3016208458","https://openalex.org/W4214632698","https://openalex.org/W4289538441","https://openalex.org/W4319347987","https://openalex.org/W4322731849","https://openalex.org/W4361862765","https://openalex.org/W4383502694","https://openalex.org/W4385188280","https://openalex.org/W4386276192","https://openalex.org/W4391648827","https://openalex.org/W4398226339","https://openalex.org/W4400490347","https://openalex.org/W4400905314","https://openalex.org/W4401062511","https://openalex.org/W4401672108","https://openalex.org/W4401824492","https://openalex.org/W4402303180","https://openalex.org/W4402351954","https://openalex.org/W4402673282","https://openalex.org/W4402703052","https://openalex.org/W4404133307","https://openalex.org/W4404295183","https://openalex.org/W4404654826","https://openalex.org/W4405601503","https://openalex.org/W4405755215","https://openalex.org/W4405755878","https://openalex.org/W4405847152","https://openalex.org/W6854568203"],"related_works":["https://openalex.org/W2386968573","https://openalex.org/W2395064349","https://openalex.org/W2034374297","https://openalex.org/W2766130412","https://openalex.org/W2382628689","https://openalex.org/W2351171996","https://openalex.org/W2983370139","https://openalex.org/W2057543190","https://openalex.org/W2131954728","https://openalex.org/W2359700606"],"abstract_inverted_index":{"With":[0],"the":[1,29,74,78,87,93,100,108,120,127,139,147,157,189,206,212,216,227,236],"increase":[2],"in":[3,90,103],"photovoltaic":[4,11,19,36,122,159,218],"installed":[5],"capacity":[6],"year":[7],"by":[8,113,136,175,182,196,243,249],"year,":[9],"accurate":[10],"power":[12,37,160,219],"prediction":[13,30,38,220,238],"is":[14,83,96,133],"of":[15,73,77,110,130,153],"great":[16],"significance":[17],"for":[18,215],"grid-connected":[20],"operation":[21],"and":[22,63,92,126,138,168,188,194,247,257],"scheduling":[23],"planning.":[24],"In":[25],"order":[26],"to":[27,85,98,145,198],"improve":[28],"accuracy,":[31],"this":[32],"paper":[33],"proposes":[34],"a":[35,116,169,200],"combination":[39],"model":[40,214],"based":[41],"on":[42],"Pearson":[43],"Correlation":[44],"Coefficient":[45],"(PCC),":[46],"Complete":[47],"Ensemble":[48],"Empirical":[49],"Mode":[50,56],"Decomposition":[51,57],"(CEEMDAN),":[52],"K-means":[53,183],"clustering,":[54],"Variational":[55],"(VMD),":[58],"Convolutional":[59],"Neural":[60],"Network":[61],"(CNN),":[62],"Bidirectional":[64],"Long":[65],"Short-Term":[66],"Memory":[67],"(BiLSTM).":[68],"By":[69],"making":[70],"full":[71],"use":[72],"symmetric":[75],"structure":[76],"BiLSTM":[79],"algorithm,":[80],"one":[81,173],"part":[82,95],"used":[84,97],"process":[86,99],"data":[88,101,112,123,161],"sequence":[89,102,111],"order,":[91],"other":[94],"reverse":[104],"order.":[105],"It":[106],"captures":[107],"characteristics":[109],"simultaneously":[114],"processing":[115],"\u2018symmetric\u2019":[117],"information.":[118],"Firstly,":[119],"historical":[121,158],"are":[124,143,162,180,192,209],"preprocessed,":[125],"correlation":[128,141],"analysis":[129],"meteorological":[131,154],"factors":[132,142],"carried":[134],"out":[135],"PCC,":[137],"high":[140],"extracted":[144],"obtain":[146],"multivariate":[148],"time":[149,174],"series":[150],"feature":[151],"matrix":[152],"factors.":[155],"Then,":[156],"decomposed":[163,193],"into":[164,211],"multiple":[165],"intrinsic":[166],"modes":[167],"residual":[170],"component":[171],"at":[172],"CEEMDAN.":[176],"The":[177],"high-frequency":[178,190],"components":[179,191],"clustered":[181],"combined":[184,237],"with":[185,226],"sample":[186],"entropy,":[187],"refined":[195],"VMD":[197],"form":[199],"multi-scale":[201],"characteristic":[202],"mode":[203],"matrix.":[204],"Finally,":[205],"obtained":[207],"features":[208],"input":[210],"CNN\u2013BiLSTM":[213],"final":[217],"results.":[221],"After":[222],"experimental":[223],"verification,":[224],"compared":[225],"traditional":[228],"single-mode":[229],"decomposition":[230],"algorithm":[231],"(such":[232],"as":[233],"CEEMDAN\u2013BiLSTM,":[234],"VMD\u2013BiLSTM),":[235],"method":[239],"proposed":[240],"reduces":[241],"MAE":[242],"more":[244,250],"than":[245,251],"0.016":[246],"RMSE":[248],"0.017,":[252],"which":[253],"shows":[254],"excellent":[255],"accuracy":[256],"stability.":[258]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}