{"id":"https://openalex.org/W7225177463","doi":"https://doi.org/10.3390/en19215213","title":"Ultra-Short-Term Wind Power Forecasting Based on Adaptive Selective Denoising and TimeMixer-Mamba","display_name":"Ultra-Short-Term Wind Power Forecasting Based on Adaptive Selective Denoising and TimeMixer-Mamba","publication_year":2026,"publication_date":"2026-11-02","ids":{"openalex":"https://openalex.org/W7225177463","doi":"https://doi.org/10.3390/en19215213"},"language":"en","primary_location":{"id":"doi:10.3390/en19215213","doi":"https://doi.org/10.3390/en19215213","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en19215213","pdf_url":null,"source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"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":"Energies","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/en19215213","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160469149","display_name":"Xiaohui Xie","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Xie","raw_affiliation_strings":["College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China","institution_ids":["https://openalex.org/I161350542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110646157","display_name":"Zhong Wen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhong Wen","raw_affiliation_strings":["College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China","institution_ids":["https://openalex.org/I161350542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079059503","display_name":"Qiujie Wang","orcid":"https://orcid.org/0000-0002-1051-9303","observed_orcids":["https://orcid.org/0000-0002-1051-9303"]},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiujie Wang","raw_affiliation_strings":["College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China"],"raw_orcid":"https://orcid.org/0000-0002-1051-9303","affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China","institution_ids":["https://openalex.org/I161350542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087902731","display_name":"Hechong Chen","orcid":"https://orcid.org/0000-0002-4213-5769","observed_orcids":["https://orcid.org/0000-0002-4213-5769"]},"institutions":[{"id":"https://openalex.org/I4405271627","display_name":"State Grid Hubei Electric Power Co., Ltd. (China)","ror":"https://ror.org/02rm87p82","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405271627"]},{"id":"https://openalex.org/I4405282457","display_name":"State Grid Hubei Electric Power Company Electric Power Research Institute","ror":"https://ror.org/05w5xs556","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4405271627","https://openalex.org/I4405282457"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hechong Chen","raw_affiliation_strings":["Electric Power Research Institute of State Grid Hubei Electric Power Co., Ltd., Wuhan 430077, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electric Power Research Institute of State Grid Hubei Electric Power Co., Ltd., Wuhan 430077, China","institution_ids":["https://openalex.org/I4405271627","https://openalex.org/I4405282457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160526878","display_name":"Kezheng Xu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kezheng Xu","raw_affiliation_strings":["College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China","institution_ids":["https://openalex.org/I161350542"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160409913","display_name":"Wentao Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wentao Zhang","raw_affiliation_strings":["College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China","institution_ids":["https://openalex.org/I161350542"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087902731","https://openalex.org/A5110646157"],"corresponding_institution_ids":["https://openalex.org/I161350542","https://openalex.org/I4405271627","https://openalex.org/I4405282457"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74167461,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"21","first_page":"5213","last_page":"5213"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9994999766349792,"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":0.9994999766349792,"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/T11276","display_name":"Solar Radiation and Photovoltaics","score":9.999999747378752e-05,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ultra-short-term-wind-power-forecasting","display_name":"ultra-short-term wind power forecasting","score":0.9990000128746033},{"id":"https://openalex.org/keywords/variational-mode-decomposition","display_name":"variational mode decomposition","score":0.8659999966621399},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"wavelet packet decomposition","score":0.9760000109672546},{"id":"https://openalex.org/keywords/improved-whale-optimization-algorithm","display_name":"improved whale optimization algorithm","score":0.7630000114440918},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"hyperparameter optimization","score":0.8529999852180481},{"id":"https://openalex.org/keywords/sample-entropy","display_name":"sample entropy","score":0.6209999918937683},{"id":"https://openalex.org/keywords/wind-power-time-series","display_name":"wind power time series","score":0.5569999814033508}],"concepts":[{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.5620999932289124},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5546000003814697},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5199999809265137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4921000003814697},{"id":"https://openalex.org/C2781084341","wikidata":"https://www.wikidata.org/wiki/Q2583670","display_name":"Wind power forecasting","level":4,"score":0.45719999074935913},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.45080000162124634},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.3952000141143799},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.3882000148296356},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3864000141620636},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.38499999046325684},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.3562999963760376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34209999442100525},{"id":"https://openalex.org/C66696666","wikidata":"https://www.wikidata.org/wiki/Q17105612","display_name":"Sample entropy","level":3,"score":0.3377000093460083},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32580000162124634},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30390000343322754},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.289000004529953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2809000015258789},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/en19215213","doi":"https://doi.org/10.3390/en19215213","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en19215213","pdf_url":null,"source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"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":"Energies","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/en19215213","doi":"https://doi.org/10.3390/en19215213","is_oa":true,"landing_page_url":"https://doi.org/10.3390/en19215213","pdf_url":null,"source":{"id":"https://openalex.org/S198098182","display_name":"Energies","issn_l":"1996-1073","issn":["1996-1073"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-140","russia-white-list-2","vabb-shw"],"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":"Energies","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.878000020980835,"display_name":"Affordable and clean energy"},{"id":"https://metadata.un.org/sdg/13","score":0.821399986743927,"display_name":"Climate action"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W3214202982","https://openalex.org/W4295278393","https://openalex.org/W4377819309","https://openalex.org/W4378894419","https://openalex.org/W4391242333","https://openalex.org/W4399010050","https://openalex.org/W4402661246","https://openalex.org/W4404386660","https://openalex.org/W4407991578","https://openalex.org/W4408762874","https://openalex.org/W4410314157","https://openalex.org/W4410711512","https://openalex.org/W4411040288","https://openalex.org/W4412665583","https://openalex.org/W4414157665","https://openalex.org/W4414652154","https://openalex.org/W4414822815","https://openalex.org/W4416501280","https://openalex.org/W7128630826","https://openalex.org/W7160922962","https://openalex.org/W7169222429"],"related_works":["https://openalex.org/W4414997100","https://openalex.org/W4399977157","https://openalex.org/W4416808342","https://openalex.org/W4415242269","https://openalex.org/W7117975511","https://openalex.org/W7124170052","https://openalex.org/W4388991805","https://openalex.org/W7126189522","https://openalex.org/W4408137415","https://openalex.org/W7135235774"],"abstract_inverted_index":{"To":[0],"improve":[1],"the":[2,28,44,101,168,171,180],"accuracy":[3],"of":[4,133,137,142,146,170],"ultra-short-term":[5,175],"wind":[6,30,88,113,176],"power":[7,31,177],"forecasting,":[8],"this":[9],"paper":[10],"proposes":[11],"a":[12,111,117,122,149],"forecasting":[13,119,178],"method":[14,107,129,173],"based":[15],"on":[16,110],"adaptive":[17,69],"selective":[18],"denoising":[19],"and":[20,47,67,84,121,139,159],"TimeMixer-Mamba.":[21],"First,":[22],"variational":[23],"mode":[24,36],"decomposition":[25,65],"(VMD)":[26],"decomposes":[27],"original":[29],"sequence":[32],"into":[33],"multiple":[34],"intrinsic":[35],"functions":[37],"(IMFs).":[38],"A":[39],"comprehensive":[40],"noise":[41],"score":[42],"combining":[43],"correlation":[45],"coefficient":[46],"sample":[48],"entropy":[49],"is":[50,75,96,108],"then":[51],"constructed":[52],"to":[53,77,99,157,163],"adaptively":[54],"identify":[55],"high-noise":[56],"IMFs,":[57],"which":[58],"are":[59],"selectively":[60],"denoised":[61],"using":[62],"wavelet":[63],"packet":[64],"(WPD)":[66],"an":[68,131,135,140],"soft":[70],"threshold":[71],"(AST).":[72],"Subsequently,":[73],"TimeMixer-Mamba":[74],"developed":[76],"capture":[78],"multiscale":[79],"temporal":[80],"patterns,":[81],"long-term":[82],"dependencies,":[83],"abrupt":[85],"changes":[86],"in":[87],"power.":[89],"The":[90,105,127,144],"improved":[91],"whale":[92],"optimization":[93],"algorithm":[94],"(IWOA)":[95],"further":[97],"employed":[98],"optimize":[100],"key":[102],"model":[103],"hyperparameters.":[104],"proposed":[106,128,172],"evaluated":[109,181],"real-world":[112],"farm":[114],"dataset":[115],"with":[116],"15-min":[118],"horizon":[120],"chronological":[123],"6:2:2":[124],"training/validation/test":[125],"split.":[126],"achieves":[130],"RMSE":[132,154],"1.89,":[134],"MAE":[136,160],"0.97,":[138],"R2":[141],"0.9855.":[143],"inclusion":[145],"WPD-AST":[147],"provides":[148],"modest":[150],"additional":[151],"improvement,":[152],"reducing":[153],"from":[155,161],"1.93":[156],"1.89":[158],"1.01":[162],"0.97.":[164],"These":[165],"results":[166],"support":[167],"effectiveness":[169],"for":[174],"within":[179],"setting.":[182]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-04T00:00:00"}
