{"id":"https://openalex.org/W4415816892","doi":"https://doi.org/10.3390/sym17111855","title":"Research and Optimization of Ultra-Short-Term Photovoltaic Power Prediction Model Based on Symmetric Parallel TCN-TST-BiGRU Architecture","display_name":"Research and Optimization of Ultra-Short-Term Photovoltaic Power Prediction Model Based on Symmetric Parallel TCN-TST-BiGRU Architecture","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4415816892","doi":"https://doi.org/10.3390/sym17111855"},"language":"en","primary_location":{"id":"doi:10.3390/sym17111855","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17111855","pdf_url":"https://www.mdpi.com/2073-8994/17/11/1855/pdf?version=1762186569","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/2073-8994/17/11/1855/pdf?version=1762186569","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022313336","display_name":"Ting Wang","orcid":"https://orcid.org/0000-0002-3712-490X"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tengjie Wang","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zian Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zian Gong","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100462286","display_name":"Zhiyuan Wang","orcid":"https://orcid.org/0000-0002-2755-4172"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Wang","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072686163","display_name":"Yuxi Liu","orcid":"https://orcid.org/0009-0004-2659-1619"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxi Liu","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101500888","display_name":"Yahong Ma","orcid":"https://orcid.org/0000-0001-7856-2052"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yahong Ma","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431141","display_name":"Feng Wang","orcid":"https://orcid.org/0000-0001-7428-2336"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Wang","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China","Xi\u2019an Key Laboratory of Intelligent Sensing and Autonomous Navigation for Low Altitude Vehicles, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]},{"raw_affiliation_string":"Xi\u2019an Key Laboratory of Intelligent Sensing and Autonomous Navigation for Low Altitude Vehicles, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100617097","display_name":"Jing Li","orcid":"https://orcid.org/0000-0002-9283-3821"},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100431141","https://openalex.org/A5101500888"],"corresponding_institution_ids":["https://openalex.org/I4210162994"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.9057,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.89981296,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"17","issue":"11","first_page":"1855","last_page":"1855"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.7858999967575073,"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":0.7858999967575073,"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":0.12300000339746475,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.01759999990463257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/photovoltaic-system","display_name":"Photovoltaic system","score":0.6011000275611877},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.5486000180244446},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5241000056266785},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.45089998841285706},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4284999966621399},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.420199990272522},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.3971000015735626},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.39169999957084656},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3853999972343445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7235000133514404},{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.6011000275611877},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.5486000180244446},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5241000056266785},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.45089998841285706},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4203999936580658},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.3971000015735626},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3853999972343445},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3319000005722046},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3098999857902527},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C2778229166","wikidata":"https://www.wikidata.org/wiki/Q8290","display_name":"Phasor measurement unit","level":5,"score":0.2644999921321869},{"id":"https://openalex.org/C36877392","wikidata":"https://www.wikidata.org/wiki/Q1229571","display_name":"Distributed power","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.257999986410141},{"id":"https://openalex.org/C9695528","wikidata":"https://www.wikidata.org/wiki/Q7556707","display_name":"Solar irradiance","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C45872418","wikidata":"https://www.wikidata.org/wiki/Q5318966","display_name":"Dynamic demand","level":3,"score":0.25440001487731934},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/sym17111855","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17111855","pdf_url":"https://www.mdpi.com/2073-8994/17/11/1855/pdf?version=1762186569","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/sym17111855","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17111855","pdf_url":"https://www.mdpi.com/2073-8994/17/11/1855/pdf?version=1762186569","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":[{"id":"https://openalex.org/F4320335869","display_name":"National Social Science Fund of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415816892.pdf","grobid_xml":"https://content.openalex.org/works/W4415816892.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"(1)":[0],"Background:":[1],"Ultra-short-term":[2],"photovoltaic":[3],"(PV)":[4],"power":[5,62,120,157],"prediction":[6,19],"is":[7,96,183],"crucial":[8],"for":[9,210],"optimizing":[10],"grid":[11,217],"scheduling":[12],"and":[13,28,51,78,85,102,127,135,143,179,185,192,204,216],"enhancing":[14],"energy":[15],"utilization":[16],"efficiency.":[17,206],"Existing":[18],"methods":[20],"face":[21],"challenges":[22],"of":[23,118,190],"missing":[24,87],"data,":[25],"noise":[26,84],"interference,":[27],"insufficient":[29],"accuracy.":[30],"(2)":[31],"Methods:":[32],"This":[33,110],"study":[34],"proposes":[35],"a":[36,65,154,200],"single-step":[37],"hybrid":[38],"neural":[39],"network":[40],"model":[41,173],"integrating":[42],"Temporal":[43,47],"Convolutional":[44],"Network":[45],"(TCN),":[46],"Shift":[48],"Transformer":[49],"(TST),":[50],"Bidirectional":[52],"Gated":[53],"Recurrent":[54],"Unit":[55],"(BiGRU)":[56],"to":[57,82],"achieve":[58],"high-precision":[59],"15-minute-ahead":[60],"PV":[61,119,156,211],"prediction,":[63],"with":[64,68,159],"design":[66],"aligned":[67],"symmetry":[69,117],"principles.":[70],"Data":[71],"preprocessing":[72],"uses":[73],"Variational":[74],"Mode":[75],"Decomposition":[76],"(VMD)":[77],"random":[79],"forest":[80],"interpolation":[81],"suppress":[83],"repair":[86],"values.":[88],"A":[89],"symmetric":[90,111,122],"parallel":[91],"dual-branch":[92],"feature":[93,141],"extraction":[94],"module":[95],"built:":[97],"TCN-TST":[98],"extracts":[99],"local":[100],"dynamics":[101],"long-term":[103],"dependencies,":[104],"while":[105],"BiGRU":[106],"captures":[107],"global":[108],"features.":[109],"structure":[112],"matches":[113],"the":[114,172,181],"intra-day":[115],"periodic":[116],"(e.g.,":[121],"irradiance":[123],"patterns":[124],"around":[125],"noon)":[126],"avoids":[128],"bias":[129],"from":[130,153],"single-branch":[131],"models.":[132],"Tensor":[133],"concatenation":[134],"an":[136],"adaptive":[137],"attention":[138],"mechanism":[139],"realize":[140],"fusion":[142],"dynamic":[144],"weighted":[145],"output.":[146],"(3)":[147],"Results:":[148],"Experiments":[149],"on":[150],"real":[151],"data":[152],"Xinjiang":[155],"station,":[158],"hyperparameter":[160],"optimization":[161],"(BiGRU":[162],"units,":[163],"activation":[164],"function,":[165],"TCN":[166,191],"kernels,":[167],"TST":[168],"parameters),":[169],"show":[170],"that":[171,189],"outperforms":[174],"comparative":[175],"models":[176],"in":[177],"MAE":[178,182],"R2\u2014e.g.,":[180],"26.53%":[184],"18.41%":[186],"lower":[187],"than":[188],"Transforme.":[193],"(4)":[194],"Conclusions:":[195],"The":[196],"proposed":[197],"method":[198],"achieves":[199],"balance":[201],"between":[202],"accuracy":[203],"computational":[205],"It":[207],"provides":[208],"references":[209],"station":[212],"operation,":[213],"system":[214],"scheduling,":[215],"stability.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-11-03T00:00:00"}