{"id":"https://openalex.org/W2991651742","doi":"https://doi.org/10.1109/smartgridcomm.2019.8909760","title":"Wind Power Scenario Generation for Microgrid Day-Ahead Scheduling Using Sequential Generative Adversarial Networks","display_name":"Wind Power Scenario Generation for Microgrid Day-Ahead Scheduling Using Sequential Generative Adversarial Networks","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2991651742","doi":"https://doi.org/10.1109/smartgridcomm.2019.8909760","mag":"2991651742"},"language":"en","primary_location":{"id":"doi:10.1109/smartgridcomm.2019.8909760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2019.8909760","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","raw_type":"proceedings-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":"https://openalex.org/A5000349516","display_name":"Junkai Liang","orcid":"https://orcid.org/0000-0002-2509-4985"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junkai Liang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033721973","display_name":"Wenyuan Tang","orcid":"https://orcid.org/0000-0001-6307-2085"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenyuan Tang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000349516"],"corresponding_institution_ids":["https://openalex.org/I137902535"],"apc_list":null,"apc_paid":null,"fwci":0.1192,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.48519893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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/T10424","display_name":"Electric Power System Optimization","score":0.9965000152587891,"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/T11185","display_name":"Integrated Energy Systems Optimization","score":0.9934999942779541,"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/computer-science","display_name":"Computer science","score":0.7428981065750122},{"id":"https://openalex.org/keywords/microgrid","display_name":"Microgrid","score":0.6364978551864624},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5738973617553711},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.5499569177627563},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5299645066261292},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4950386583805084},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4572058320045471},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4522746205329895},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4522165060043335},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.43395477533340454},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4330708980560303},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4257954955101013},{"id":"https://openalex.org/keywords/electricity-generation","display_name":"Electricity generation","score":0.4142729938030243},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.41240930557250977},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.347348153591156},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3000853955745697},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.28320759534835815},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19224917888641357}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7428981065750122},{"id":"https://openalex.org/C2776784348","wikidata":"https://www.wikidata.org/wiki/Q5762595","display_name":"Microgrid","level":3,"score":0.6364978551864624},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5738973617553711},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.5499569177627563},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5299645066261292},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4950386583805084},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4572058320045471},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4522746205329895},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4522165060043335},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.43395477533340454},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4330708980560303},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4257954955101013},{"id":"https://openalex.org/C423512","wikidata":"https://www.wikidata.org/wiki/Q383973","display_name":"Electricity generation","level":3,"score":0.4142729938030243},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.41240930557250977},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.347348153591156},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3000853955745697},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28320759534835815},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19224917888641357},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smartgridcomm.2019.8909760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2019.8909760","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1971474913","https://openalex.org/W2009012905","https://openalex.org/W2074911163","https://openalex.org/W2099471712","https://openalex.org/W2101457442","https://openalex.org/W2114471530","https://openalex.org/W2147526029","https://openalex.org/W2148402438","https://openalex.org/W2345777279","https://openalex.org/W2592036976","https://openalex.org/W2739824434","https://openalex.org/W2754252319","https://openalex.org/W2806443828","https://openalex.org/W2808628700","https://openalex.org/W2883904934","https://openalex.org/W2901316757","https://openalex.org/W2921491216","https://openalex.org/W2964121744","https://openalex.org/W2964268978","https://openalex.org/W4320013936","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W1574359403","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655"],"abstract_inverted_index":{"With":[0],"the":[1,5,15,28,31,54,57,61,68,80,86,89,97,101,111,123,131],"rapid":[2],"increase":[3],"in":[4,136,155],"distributed":[6],"wind":[7,43,112,134],"generation,":[8],"considerable":[9],"efforts":[10],"have":[11],"been":[12],"devoted":[13],"to":[14,78,85,110],"microgrid":[16],"day-ahead":[17],"scheduling.":[18],"The":[19,103,119,140],"effectiveness":[20],"of":[21,30,70,100,115,133,157],"these":[22],"methods":[23],"will":[24],"highly":[25],"depend":[26],"on":[27],"selection":[29],"uncertainty":[32],"set.":[33],"In":[34,83],"this":[35],"work,":[36],"we":[37],"propose":[38],"a":[39,137],"distribution-free":[40],"approach":[41],"for":[42],"power":[44,113,135],"scenario":[45,105],"generation":[46,106],"using":[47],"sequential":[48],"generative":[49,71],"adversarial":[50,72],"networks.":[51],"To":[52],"capture":[53],"temporal":[55],"correlation,":[56],"proposed":[58,90,104],"model":[59,91,128],"adopts":[60],"long":[62],"short-term":[63],"memory":[64],"architecture":[65],"and":[66,95,151],"uses":[67],"concept":[69],"networks":[73],"coupled":[74],"with":[75,145],"reinforcement":[76],"learning":[77,81],"guide":[79],"process.":[82],"contrast":[84],"existing":[87],"methods,":[88],"avoids":[92],"manual":[93],"labeling":[94],"captures":[96],"complex":[98],"dynamics":[99],"weather.":[102],"method":[107],"is":[108],"applied":[109],"dataset":[114],"Bonneville":[116],"Power":[117],"Administration.":[118],"results":[120],"indicate":[121],"that":[122],"scenarios":[124,142],"generated":[125,141],"by":[126,148],"our":[127],"can":[129],"characterize":[130],"variability":[132],"better":[138],"manner.":[139],"are":[143],"compared":[144],"those":[146],"produced":[147],"Gaussian":[149],"distribution":[150],"kernel":[152],"density":[153],"estimation,":[154],"terms":[156],"two":[158],"statistical":[159],"scores.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}