{"id":"https://openalex.org/W3196472152","doi":"https://doi.org/10.1109/access.2021.3108453","title":"Spatial-Temporal Genetic-Based Attention Networks for Short-Term Photovoltaic Power Forecasting","display_name":"Spatial-Temporal Genetic-Based Attention Networks for Short-Term Photovoltaic Power Forecasting","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3196472152","doi":"https://doi.org/10.1109/access.2021.3108453","mag":"3196472152"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3108453","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3108453","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09524585.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09524585.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100974394","display_name":"Tao Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Fan","raw_affiliation_strings":["State Grid Corporation of China, Beijing 100031, China"],"affiliations":[{"raw_affiliation_string":"State Grid Corporation of China, Beijing 100031, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073081338","display_name":"Tao Sun","orcid":"https://orcid.org/0000-0003-2220-930X"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Sun","raw_affiliation_strings":["State Grid e-commerce Co., Ltd, Beijing 100053, China"],"affiliations":[{"raw_affiliation_string":"State Grid e-commerce Co., Ltd, Beijing 100053, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100699087","display_name":"Hu Liu","orcid":"https://orcid.org/0000-0001-9894-2511"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Liu","raw_affiliation_strings":["State Grid Corporation of China, Beijing 100031, China"],"affiliations":[{"raw_affiliation_string":"State Grid Corporation of China, Beijing 100031, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102942071","display_name":"Xiangying Xie","orcid":"https://orcid.org/0000-0001-9375-6496"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangying Xie","raw_affiliation_strings":["State Grid e-commerce Co., Ltd, Beijing 100053, China"],"affiliations":[{"raw_affiliation_string":"State Grid e-commerce Co., Ltd, Beijing 100053, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075239269","display_name":"Zhixiong Na","orcid":"https://orcid.org/0000-0002-5742-1338"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixiong Na","raw_affiliation_strings":["State Grid e-commerce Co., Ltd, Beijing 100053, China. (e-mail: hellonazx@163.com)","State Grid e-commerce Co., Ltd, Beijing 100053, China,"],"affiliations":[{"raw_affiliation_string":"State Grid e-commerce Co., Ltd, Beijing 100053, China. (e-mail: hellonazx@163.com)","institution_ids":["https://openalex.org/I17442442"]},{"raw_affiliation_string":"State Grid e-commerce Co., Ltd, Beijing 100053, China,","institution_ids":["https://openalex.org/I17442442"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100974394"],"corresponding_institution_ids":["https://openalex.org/I17442442"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.0396,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.89079786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"138762","last_page":"138774"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":1.0,"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":1.0,"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":0.9995999932289124,"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":0.9986000061035156,"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/computer-science","display_name":"Computer science","score":0.7552427053451538},{"id":"https://openalex.org/keywords/photovoltaic-system","display_name":"Photovoltaic system","score":0.7375754117965698},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6284013986587524},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4921554923057556},{"id":"https://openalex.org/keywords/solar-irradiance","display_name":"Solar irradiance","score":0.46782058477401733},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41938716173171997},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41216689348220825},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39537811279296875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3891916871070862},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3808889389038086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28222888708114624},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.1411048173904419},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10167613625526428},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08092883229255676}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7552427053451538},{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.7375754117965698},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6284013986587524},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4921554923057556},{"id":"https://openalex.org/C9695528","wikidata":"https://www.wikidata.org/wiki/Q7556707","display_name":"Solar irradiance","level":2,"score":0.46782058477401733},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41938716173171997},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41216689348220825},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39537811279296875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3891916871070862},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3808889389038086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28222888708114624},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.1411048173904419},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10167613625526428},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08092883229255676},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3108453","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3108453","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09524585.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4d03b0abb30c4fe78c301778ff4e333a","is_oa":true,"landing_page_url":"https://doaj.org/article/4d03b0abb30c4fe78c301778ff4e333a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 138762-138774 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3108453","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3108453","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09524585.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G443774039","display_name":null,"funder_award_id":"SGTJDK00DYJS2000148","funder_id":"https://openalex.org/F4320326707","funder_display_name":"State Grid Corporation of China"},{"id":"https://openalex.org/G7887336454","display_name":null,"funder_award_id":"2018YFB1500800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320326707","display_name":"State Grid Corporation of China","ror":"https://ror.org/05twwhs70"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3196472152.pdf","grobid_xml":"https://content.openalex.org/works/W3196472152.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1902237438","https://openalex.org/W2002841906","https://openalex.org/W2018637874","https://openalex.org/W2026844045","https://openalex.org/W2064675550","https://openalex.org/W2327473694","https://openalex.org/W2513823490","https://openalex.org/W2590910929","https://openalex.org/W2604812710","https://openalex.org/W2610219179","https://openalex.org/W2627005058","https://openalex.org/W2751698537","https://openalex.org/W2796179209","https://openalex.org/W2884441021","https://openalex.org/W2897143050","https://openalex.org/W2899789913","https://openalex.org/W2905035404","https://openalex.org/W2905222110","https://openalex.org/W2912623183","https://openalex.org/W2912764223","https://openalex.org/W2920873814","https://openalex.org/W2925435752","https://openalex.org/W2949062675","https://openalex.org/W2949335953","https://openalex.org/W2954884550","https://openalex.org/W2963151450","https://openalex.org/W2963311488","https://openalex.org/W2969690146","https://openalex.org/W2978584985","https://openalex.org/W2982118449","https://openalex.org/W2984886732","https://openalex.org/W2990430732","https://openalex.org/W2995861305","https://openalex.org/W3014822860","https://openalex.org/W3034377024","https://openalex.org/W3036614699","https://openalex.org/W3038628583","https://openalex.org/W3047993744","https://openalex.org/W3103720336","https://openalex.org/W3126804380","https://openalex.org/W6666761814"],"related_works":["https://openalex.org/W2386968573","https://openalex.org/W2395064349","https://openalex.org/W2034374297","https://openalex.org/W2766130412","https://openalex.org/W4391621807","https://openalex.org/W2382628689","https://openalex.org/W2351171996","https://openalex.org/W2983370139","https://openalex.org/W2057543190","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Photovoltaic":[0],"(PV)":[1],"output":[2],"power":[3,18,26,171],"is":[4,154],"significantly":[5],"random":[6],"and":[7,36,63,82,93,126,130,143,169],"fluctuating":[8],"due":[9],"to":[10,13,71,77,89,108,138,144],"its":[11],"sensitivity":[12],"meteorological":[14,98,167],"factors,":[15],"making":[16],"PV":[17,25,40,175,194],"forecasting":[19,27,134],"a":[20,29,49,59,64,84,164,170],"big":[21],"challenge.":[22],"Accurate":[23],"short-term":[24],"plays":[28],"crucial":[30],"role":[31],"for":[32,117],"the":[33,46,73,79,91,105,110,185],"stable":[34],"operation":[35,129],"maintenance":[37],"management":[38],"of":[39,58,174],"systems.":[41,195],"To":[42],"achieve":[43],"this":[44],"target,":[45],"paper":[47],"proposes":[48],"novel":[50],"Spatial-Temporal":[51],"Genetic-based":[52],"Attention":[53],"Networks":[54],"(STGANet),":[55],"which":[56,132],"consists":[57],"spatial-temporal":[60],"module":[61,67],"(STM)":[62],"genetic-based":[65,128],"attention":[66],"(GAM).":[68],"STM":[69],"serves":[70],"predict":[72],"missing":[74],"solar":[75],"irradiance":[76],"support":[78],"generation":[80,172],"forecast,":[81],"contains":[83],"graph":[85],"convolutional":[86],"neural":[87],"network":[88,111],"learn":[90],"spatial":[92],"temporal":[94],"dependencies":[95],"between":[96],"historical":[97,166],"data,":[99],"while":[100],"using":[101,163],"dilated":[102],"convolution":[103],"as":[104,136],"non-linear":[106],"part":[107],"simplify":[109],"structure.":[112],"The":[113,152,180],"GAM":[114],"efficiently":[115],"explores":[116],"potential":[118],"relationships":[119],"in":[120,148,177,193],"input":[121],"features":[122],"with":[123,159],"attentional":[124],"mechanism":[125],"uses":[127],"LSTM":[131],"takes":[133],"error":[135],"reference":[137],"find":[139],"global":[140],"optimal":[141,150],"solutions":[142],"avoid":[145],"getting":[146],"trapped":[147],"local":[149],"solutions.":[151],"model":[153,187],"verified":[155],"through":[156],"comparative":[157],"experiment":[158],"several":[160],"benchmark":[161],"models":[162],"real-world":[165],"dataset":[168,173],"plants":[176],"southeastern":[178],"China.":[179],"results":[181],"have":[182],"illustrated":[183],"that":[184],"proposed":[186],"can":[188],"provide":[189],"better":[190],"prediction":[191],"performance":[192]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
