{"id":"https://openalex.org/W4415971129","doi":"https://doi.org/10.1109/tii.2025.3623559","title":"Physics-Informed Adaptive-Weight NBeatsx for Short-Term Wind Power Forecasting","display_name":"Physics-Informed Adaptive-Weight NBeatsx for Short-Term Wind Power Forecasting","publication_year":2025,"publication_date":"2025-11-06","ids":{"openalex":"https://openalex.org/W4415971129","doi":"https://doi.org/10.1109/tii.2025.3623559"},"language":null,"primary_location":{"id":"doi:10.1109/tii.2025.3623559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3623559","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chunyu Li","orcid":"https://orcid.org/0009-0004-9516-0521"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyu Li","raw_affiliation_strings":["Shandong Provincial Engineering Research Center of Intelligent Sensing and Measurement and Control Technology, College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"raw_orcid":"https://orcid.org/0009-0004-9516-0521","affiliations":[{"raw_affiliation_string":"Shandong Provincial Engineering Research Center of Intelligent Sensing and Measurement and Control Technology, College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100646407","display_name":"Li Sheng","orcid":"https://orcid.org/0000-0003-2940-209X"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Sheng","raw_affiliation_strings":["Shandong Provincial Engineering Research Center of Intelligent Sensing and Measurement and Control Technology, College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0003-2940-209X","affiliations":[{"raw_affiliation_string":"Shandong Provincial Engineering Research Center of Intelligent Sensing and Measurement and Control Technology, College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015669906","display_name":"Xiaopeng Xi","orcid":"https://orcid.org/0000-0003-2909-2642"},"institutions":[{"id":"https://openalex.org/I75778554","display_name":"Federico Santa Mar\u00eda Technical University","ror":"https://ror.org/05510vn56","country_code":"CL","type":"education","lineage":["https://openalex.org/I75778554"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Xiaopeng Xi","raw_affiliation_strings":["Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso, Chile"],"raw_orcid":"https://orcid.org/0000-0003-2909-2642","affiliations":[{"raw_affiliation_string":"Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso, Chile","institution_ids":["https://openalex.org/I75778554"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057357799","display_name":"Maiying Zhong","orcid":"https://orcid.org/0000-0001-5800-1637"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maiying Zhong","raw_affiliation_strings":["College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0001-5800-1637","affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3064,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56827356,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"22","issue":"2","first_page":"1129","last_page":"1140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9761999845504761,"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"}},"topics":[{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9761999845504761,"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/T10740","display_name":"Wind Turbine Control Systems","score":0.0052999998442828655,"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/T10680","display_name":"Wind Energy Research and Development","score":0.003599999938160181,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/wind-power-forecasting","display_name":"Wind power forecasting","score":0.8091999888420105},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.7530999779701233},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.5717999935150146},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5551000237464905},{"id":"https://openalex.org/keywords/turbine","display_name":"Turbine","score":0.521399974822998},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5171999931335449},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4997999966144562},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.40779998898506165},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3903000056743622}],"concepts":[{"id":"https://openalex.org/C2781084341","wikidata":"https://www.wikidata.org/wiki/Q2583670","display_name":"Wind power forecasting","level":4,"score":0.8091999888420105},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.7530999779701233},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6072999835014343},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.5717999935150146},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5551000237464905},{"id":"https://openalex.org/C2778449969","wikidata":"https://www.wikidata.org/wiki/Q130760","display_name":"Turbine","level":2,"score":0.521399974822998},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5171999931335449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4997999966144562},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.40779998898506165},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3903000056743622},{"id":"https://openalex.org/C105637607","wikidata":"https://www.wikidata.org/wiki/Q1786258","display_name":"Drivetrain","level":3,"score":0.3837999999523163},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.3675000071525574},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.3456999957561493},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.31700000166893005},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C2780848588","wikidata":"https://www.wikidata.org/wiki/Q210494","display_name":"Power Balance","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2930999994277954},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C2777831296","wikidata":"https://www.wikidata.org/wiki/Q12518","display_name":"Tower","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27619999647140503},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2712000012397766},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.262800008058548},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2025.3623559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3623559","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3501331844","display_name":null,"funder_award_id":"ZR2025ZD02","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G5342345635","display_name":null,"funder_award_id":"62173343","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5538391834","display_name":null,"funder_award_id":"ZR2024MF072","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G7308361541","display_name":null,"funder_award_id":"62033008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G811874178","display_name":null,"funder_award_id":"62233012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2980011983","https://openalex.org/W2980224341","https://openalex.org/W3004151245","https://openalex.org/W3020265068","https://openalex.org/W3154291377","https://openalex.org/W3160258528","https://openalex.org/W3201318708","https://openalex.org/W4200209943","https://openalex.org/W4220699563","https://openalex.org/W4282971608","https://openalex.org/W4285115901","https://openalex.org/W4313443611","https://openalex.org/W4316661065","https://openalex.org/W4318997277","https://openalex.org/W4321485251","https://openalex.org/W4385245566","https://openalex.org/W4385819789","https://openalex.org/W4386968812","https://openalex.org/W4388249091","https://openalex.org/W4388895179","https://openalex.org/W4390488899","https://openalex.org/W4390512291","https://openalex.org/W4392658546","https://openalex.org/W4396842144","https://openalex.org/W4399561201","https://openalex.org/W4401811317","https://openalex.org/W4402738086","https://openalex.org/W4404479779","https://openalex.org/W4406388002","https://openalex.org/W4407847716","https://openalex.org/W4408095137","https://openalex.org/W4408357912","https://openalex.org/W4408358224","https://openalex.org/W4408362988","https://openalex.org/W4411127501"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"and":[1,35,105,121,138,191,199],"physically":[2],"interpretable":[3],"wind":[4,32,41,129,136,177],"power":[5,16,42],"forecasting":[6],"(WPF)":[7],"is":[8,153,184],"crucial":[9],"for":[10,39,113,155],"ensuring":[11],"the":[12,68,76,98,115,145,160,181,188],"reliable":[13],"operation":[14],"of":[15,70,101,119,128,159,164,174,196],"grid":[17],"systems.":[18],"Wind":[19],"turbines":[20],"have":[21,48],"operational":[22,126],"characteristics":[23],"significantly":[24,185],"influenced":[25],"by":[26],"complex":[27],"environmental":[28],"factors,":[29],"such":[30,131],"as":[31,132],"speed":[33],"fluctuations":[34],"intermittency,":[36],"posing":[37],"challenges":[38],"precise":[40],"modeling.":[43],"Although":[44],"deep":[45,99],"learning":[46],"models":[47,190],"become":[49],"a":[50,87,109,172,175],"promising":[51],"data-driven":[52,106],"solution":[53],"in":[54,123,194],"WPF,":[55],"their":[56],"common":[57],"\u201cclosed-box\u201d":[58],"nature":[59],"makes":[60],"it":[61],"difficult":[62],"to":[63,187],"balance":[64],"forecast":[65,197],"accuracy":[66,120,198],"with":[67],"rationality":[69],"physical":[71,102],"mechanisms.":[72],"Therefore,":[73],"based":[74,170],"on":[75,171],"neural":[77],"basis":[78],"expansion":[79],"analysis":[80],"(NBEATSx)":[81],"network":[82,146],"architecture,":[83],"this":[84],"article":[85],"proposes":[86],"multistep":[88],"WPF":[89],"method,":[90],"named":[91],"physics-informed":[92],"adaptive-weight":[93],"NBEATSx.":[94],"This":[95],"method":[96,183],"realizes":[97],"integration":[100],"prior":[103],"knowledge":[104],"models,":[107],"providing":[108],"novel":[110],"technical":[111],"path":[112],"solving":[114],"joint":[116],"optimization":[117],"problem":[118],"interpretability":[122],"WPF.":[124],"The":[125,167],"constraints":[127],"turbines,":[130],"cut-in,":[133],"rated,":[134],"cut-out":[135],"speeds,":[137],"rated":[139],"power,":[140],"are":[141],"explicitly":[142],"embedded":[143],"into":[144],"structure.":[147],"A":[148],"dynamic":[149],"trainable":[150],"weighting":[151],"mechanism":[152],"leveraged":[154],"stack":[156],"outputs,":[157],"instead":[158],"traditional":[161],"aggregation":[162],"strategy":[163],"direct":[165],"summation.":[166],"experimental":[168],"results":[169],"dataset":[173],"2-MW":[176],"turbine":[178],"show":[179],"that":[180],"proposed":[182],"superior":[186],"benchmark":[189],"NBEATSx":[192],"variants":[193],"terms":[195],"robustness.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-11-06T00:00:00"}