{"id":"https://openalex.org/W4404739746","doi":"https://doi.org/10.1109/rtsi61910.2024.10761768","title":"Optimizing Partner Selection for Cooperative Solar Generation Forecasting","display_name":"Optimizing Partner Selection for Cooperative Solar Generation Forecasting","publication_year":2024,"publication_date":"2024-09-18","ids":{"openalex":"https://openalex.org/W4404739746","doi":"https://doi.org/10.1109/rtsi61910.2024.10761768"},"language":"en","primary_location":{"id":"doi:10.1109/rtsi61910.2024.10761768","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/rtsi61910.2024.10761768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI)","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/A5077007267","display_name":"Lejla Pa\u0161i\u0107","orcid":"https://orcid.org/0000-0002-1447-0252"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Lejla Pa\u0161i\u0107","raw_affiliation_strings":["Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111"],"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056256150","display_name":"Azra Pa\u0161i\u0107","orcid":"https://orcid.org/0000-0001-7443-0458"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Azra Pa\u0161i\u0107","raw_affiliation_strings":["Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111"],"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042651467","display_name":"Alija Pa\u0161\u00ed\u0107","orcid":"https://orcid.org/0000-0001-6346-496X"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Alija Pa\u0161i\u0107","raw_affiliation_strings":["Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111"],"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081387612","display_name":"J\u00f3zsef B\u0131\u0301r\u00f3","orcid":"https://orcid.org/0000-0002-9729-2702"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"J\u00f3zsef B\u00edr\u00f3","raw_affiliation_strings":["Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111"],"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Faculty of Electrical Engineering and Informatics,Budapest,Hungary,H-1111","institution_ids":["https://openalex.org/I29770179"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077007267"],"corresponding_institution_ids":["https://openalex.org/I29770179"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18933568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"248","last_page":"253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9484000205993652,"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":0.9484000205993652,"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":0.9451000094413757,"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/selection","display_name":"Selection (genetic algorithm)","score":0.6524736881256104},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5865517854690552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29110264778137207}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6524736881256104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5865517854690552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29110264778137207}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/rtsi61910.2024.10761768","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/rtsi61910.2024.10761768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI)","raw_type":"proceedings-article"},{"id":"pmh:oai:real.mtak.hu:205814","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400081","display_name":"Repository of the Academy's Library (Library of the Hungarian Academy of Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210140733","host_organization_name":"Library and Information Centre of the Hungarian Academy of Sciences","host_organization_lineage":["https://openalex.org/I4210140733"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Book Section"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1989938710","https://openalex.org/W2002016471","https://openalex.org/W2028070629","https://openalex.org/W2101234009","https://openalex.org/W2159216890","https://openalex.org/W2174610466","https://openalex.org/W2329191997","https://openalex.org/W2773629498","https://openalex.org/W2792531619","https://openalex.org/W2898511698","https://openalex.org/W2902756944","https://openalex.org/W2945102769","https://openalex.org/W2987236225","https://openalex.org/W3000604112","https://openalex.org/W4293090484"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,35],"our":[1],"previous":[2,135,186],"work":[3],"we":[4,15,38,138],"introduced":[5],"the":[6,18,29,41,48,118,126,143,151,154,161,169,182,189],"ANN-Based":[7],"Large-Scale":[8],"Cooperative":[9],"Solar":[10],"Generation":[11],"Forecasting":[12],"method,":[13],"where":[14,163],"showed":[16],"that":[17,132],"forecasting":[19,145],"accuracy":[20],"on":[21],"large-scale":[22],"models":[23],"can":[24],"be":[25],"greatly":[26],"improved":[27],"with":[28,121],"introduction":[30],"of":[31,43,51,106,153,184],"cooperation":[32,45,107,155,174,194],"between":[33,125],"partners.":[34],"this":[36,148],"work,":[37],"delve":[39],"into":[40],"importance":[42],"said":[44],"partners":[46,108],"and":[47,56,77,89],"possible":[49],"methods":[50],"their":[52],"selection.":[53],"We":[54,129],"tested":[55],"compared":[57],"five":[58],"different":[59,86,127],"approaches":[60],"-":[61,83],"random":[62],"selection,":[63],"temperature":[64,72],"based":[65,69,73,79],"K-means":[66,70],"clustering,":[67,71],"generation":[68,78,92,136,165,187],"Pearson":[74,80],"correlation":[75,81],"grouping":[76,82],"in":[84,160,181],"two":[85],"scenarios":[87],"(with":[88],"without":[90],"added":[91,185],"data":[93,166],"to":[94,173,178,193,198],"weather":[95],"data),":[96],"utilizing":[97,134],"an":[98],"Artificial":[99],"Neural":[100],"Network":[101],"for":[102,117],"prediction.":[103],"The":[104],"optimization":[105],"yielded":[109],"error":[110,170,190],"reductions":[111],"even":[112],"as":[113,115,157,159],"high":[114],"70%":[116],"best-performing":[119],"solutions,":[120],"clear":[122],"differences":[123],"outlined":[124],"approaches.":[128],"additionally":[130],"observed":[131],"when":[133],"data,":[137,188],"could":[139],"not":[140],"only":[141],"improve":[142],"overall":[144],"accuracy,":[146],"but":[147],"also":[149],"boosted":[150],"benefits":[152],"method":[156],"well,":[158],"case":[162,183],"no":[164],"was":[167],"used,":[168],"reduction":[171,191],"due":[172,192],"ranged":[175],"from":[176,196],"7.92%":[177],"50.74%,":[179],"whereas":[180],"spanned":[195],"22.6%":[197],"69.93%.":[199]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
