{"id":"https://openalex.org/W7164812031","doi":"https://doi.org/10.1016/j.cor.2026.107584","title":"Risk-averse wind farms placement via quantile constraint learning","display_name":"Risk-averse wind farms placement via quantile constraint learning","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164812031","doi":"https://doi.org/10.1016/j.cor.2026.107584"},"language":"en","primary_location":{"id":"doi:10.1016/j.cor.2026.107584","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cor.2026.107584","pdf_url":null,"source":{"id":"https://openalex.org/S173256270","display_name":"Computers & Operations Research","issn_l":"0305-0548","issn":["0305-0548","1873-765X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers &amp; Operations Research","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.cor.2026.107584","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101465926","display_name":"Wenxiu Feng","orcid":"https://orcid.org/0000-0002-1880-9727"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Wenxiu Feng","raw_affiliation_strings":["Department of Statistics, University Carlos III of Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0002-1880-9727","affiliations":[{"raw_affiliation_string":"Department of Statistics, University Carlos III of Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003482493","display_name":"Ant\u00f3nio Alc\u00e1ntara","orcid":"https://orcid.org/0000-0002-3306-2246"},"institutions":[{"id":"https://openalex.org/I4403386682","display_name":"CUNEF Universidad","ror":"https://ror.org/02web8j86","country_code":null,"type":"education","lineage":["https://openalex.org/I4403386682"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Alc\u00e1ntara","raw_affiliation_strings":["Department of Quantitative Methods, CUNEF Universidad, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Quantitative Methods, CUNEF Universidad, Spain","institution_ids":["https://openalex.org/I4403386682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084339169","display_name":"Carlos Ruiz","orcid":"https://orcid.org/0000-0003-1663-1061"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Carlos Ruiz","raw_affiliation_strings":["Department of Statistics, University Carlos III of Madrid, Spain","UC3M-BS Institute for Financial Big Data (IFiBiD), University Carlos III of Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0003-1663-1061","affiliations":[{"raw_affiliation_string":"Department of Statistics, University Carlos III of Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"UC3M-BS Institute for Financial Big Data (IFiBiD), University Carlos III of Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101465926"],"corresponding_institution_ids":["https://openalex.org/I50357001"],"apc_list":{"value":3210,"currency":"USD","value_usd":3210},"apc_paid":{"value":3210,"currency":"USD","value_usd":3210},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.88092472,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"194","issue":null,"first_page":"107584","last_page":"107584"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10680","display_name":"Wind Energy Research and Development","score":0.5112000107765198,"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"}},"topics":[{"id":"https://openalex.org/T10680","display_name":"Wind Energy Research and Development","score":0.5112000107765198,"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"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.23420000076293945,"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":0.05939999967813492,"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/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.6134999990463257},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5734999775886536},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5126000046730042},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.47999998927116394},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.46389999985694885},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42879998683929443},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.3919000029563904},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.38359999656677246},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.3427000045776367},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.3366999924182892}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6151000261306763},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.6134999990463257},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5734999775886536},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.550599992275238},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5126000046730042},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.47999998927116394},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.46389999985694885},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.3919000029563904},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.38359999656677246},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C202655437","wikidata":"https://www.wikidata.org/wiki/Q7231728","display_name":"Portfolio optimization","level":3,"score":0.3156000077724457},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C8735168","wikidata":"https://www.wikidata.org/wiki/Q61637704","display_name":"Offshore wind power","level":3,"score":0.3052000105381012},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.3027999997138977},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C9233905","wikidata":"https://www.wikidata.org/wiki/Q3276328","display_name":"Bidding","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C180916674","wikidata":"https://www.wikidata.org/wiki/Q3711935","display_name":"Diversification (marketing strategy)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C203332170","wikidata":"https://www.wikidata.org/wiki/Q6334079","display_name":"Multivariate interpolation","level":3,"score":0.26499998569488525},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C33441834","wikidata":"https://www.wikidata.org/wiki/Q693004","display_name":"Transmission line","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C140311924","wikidata":"https://www.wikidata.org/wiki/Q200928","display_name":"Electric power transmission","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.cor.2026.107584","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cor.2026.107584","pdf_url":null,"source":{"id":"https://openalex.org/S173256270","display_name":"Computers & Operations Research","issn_l":"0305-0548","issn":["0305-0548","1873-765X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers &amp; Operations Research","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.cor.2026.107584","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cor.2026.107584","pdf_url":null,"source":{"id":"https://openalex.org/S173256270","display_name":"Computers & Operations Research","issn_l":"0305-0548","issn":["0305-0548","1873-765X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers &amp; Operations Research","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.902823805809021,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320323770","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W347506559","https://openalex.org/W1845886676","https://openalex.org/W1968131695","https://openalex.org/W1971474913","https://openalex.org/W1989245622","https://openalex.org/W1989425731","https://openalex.org/W2011949083","https://openalex.org/W2012923650","https://openalex.org/W2083172569","https://openalex.org/W2509157185","https://openalex.org/W2767196798","https://openalex.org/W2800222242","https://openalex.org/W2889429719","https://openalex.org/W2946962413","https://openalex.org/W2974004735","https://openalex.org/W3087772159","https://openalex.org/W3162897351","https://openalex.org/W3203468434","https://openalex.org/W4224246843","https://openalex.org/W4387730174","https://openalex.org/W4388473349","https://openalex.org/W4390414905","https://openalex.org/W4396621372","https://openalex.org/W4400139458","https://openalex.org/W4406961020","https://openalex.org/W4410050203","https://openalex.org/W4415829199"],"related_works":[],"abstract_inverted_index":{"Wind":[0],"farm":[1,221],"placement":[2,86],"arranges":[3],"the":[4,7,54,84,97,110,128,133,180,190,210],"size":[5],"and":[6,28,162,223],"location":[8],"of":[9,57,100,218],"multiple":[10],"wind":[11,24,58,220],"farms":[12],"within":[13],"a":[14,44,49,91,120,216],"given":[15],"region.":[16],"The":[17,145],"power":[18],"output":[19],"is":[20],"highly":[21],"related":[22],"to":[23,187,196,198,201],"speed":[25],"on":[26,142,152],"spatial":[27,160],"temporal":[29],"levels,":[30],"which":[31],"can":[32,70,214],"be":[33,71],"modeled":[34],"by":[35],"advanced":[36],"data-driven":[37],"approaches.":[38],"To":[39],"this":[40],"end,":[41],"we":[42,170,174],"use":[43,114],"probabilistic":[45],"neural":[46,61],"network":[47,62],"as":[48,73,90,106],"surrogate":[50],"that":[51,68,127,148,172,209],"accounts":[52],"for":[53,227],"spatiotemporal":[55],"correlations":[56],"speed.":[59],"This":[60],"uses":[63],"ReLU":[64],"activation":[65],"functions":[66],"so":[67],"it":[69],"reformulated":[72],"mixed-integer":[74],"linear":[75],"constraints":[76,82],"(constraint":[77],"learning).":[78],"We":[79,113,125],"embed":[80],"these":[81],"into":[83,179],"risk-averse":[85,143,149,182,228],"decision":[87],"problem,":[88,181],"formulated":[89],"two-stage":[92],"stochastic":[93],"optimization":[94],"problem.":[95],"Specifically,":[96],"conditional":[98],"quantiles":[99],"total":[101],"electricity":[102],"production":[103],"are":[104,140,194],"regarded":[105],"recursive":[107],"decisions":[108],"in":[109,123,166],"second":[111],"stage.":[112],"real":[115],"high-resolution":[116],"regional":[117,219],"data":[118],"from":[119],"northern":[121],"region":[122],"Spain.":[124],"validate":[126],"constraint":[129],"learning":[130],"approach":[131,213],"outperforms":[132],"classical":[134],"bilinear":[135],"interpolation":[136],"method.":[137],"Numerical":[138],"experiments":[139],"implemented":[141],"investors.":[144,229],"results":[146,207],"indicate":[147],"investors":[150,183,193],"concentrate":[151],"dominant":[153],"sites":[154],"with":[155],"strong":[156],"wind,":[157],"while":[158],"exhibiting":[159],"diversification":[161],"sensitive":[163],"capacity":[164],"spread":[165],"non-dominant":[167],"sites.":[168],"Furthermore,":[169],"show":[171],"when":[173],"introduce":[175],"transmission":[176],"line":[177],"costs":[178],"favor":[184],"locations":[185,200],"closer":[186],"substations.":[188],"On":[189],"contrary,":[191],"risk-neutral":[192],"willing":[195],"move":[197],"further":[199,224],"achieve":[202],"higher":[203],"expected":[204],"profits.":[205],"Our":[206],"conclude":[208],"proposed":[211],"novel":[212],"tackle":[215],"portfolio":[217],"placements":[222],"provide":[225],"guidance":[226]},"counts_by_year":[],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2026-06-16T00:00:00"}
