{"id":"https://openalex.org/W4313459177","doi":"https://doi.org/10.1109/dtpi55838.2022.9998947","title":"Evolutionary Deep Reinforcement Learning for Volt-VAR Control in Distribution Network","display_name":"Evolutionary Deep Reinforcement Learning for Volt-VAR Control in Distribution Network","publication_year":2022,"publication_date":"2022-10-24","ids":{"openalex":"https://openalex.org/W4313459177","doi":"https://doi.org/10.1109/dtpi55838.2022.9998947"},"language":"en","primary_location":{"id":"doi:10.1109/dtpi55838.2022.9998947","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dtpi55838.2022.9998947","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","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/A5043042095","display_name":"Ruiqi Si","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruiqi Si","raw_affiliation_strings":["School of Electrical Engineering and Automation, Wuhan University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018951250","display_name":"Tianlu Gao","orcid":"https://orcid.org/0000-0003-0625-7002"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianlu Gao","raw_affiliation_strings":["School of Electrical Engineering and Automation, Wuhan University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068297028","display_name":"Yuxin Dai","orcid":"https://orcid.org/0000-0001-8805-7236"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Dai","raw_affiliation_strings":["School of Electrical Engineering and Automation, Wuhan University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100624468","display_name":"Yuyang Bai","orcid":"https://orcid.org/0009-0005-4363-5350"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Bai","raw_affiliation_strings":["School of Electrical Engineering and Automation, Wuhan University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102714904","display_name":"Yuqi Jiang","orcid":"https://orcid.org/0009-0007-6732-9862"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqi Jiang","raw_affiliation_strings":["School of Electrical Engineering and Automation, Wuhan University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007781850","display_name":"Jun Jason Zhang","orcid":"https://orcid.org/0000-0001-6908-2671"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["School of Electrical Engineering and Automation, Wuhan University"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Wuhan University","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5043042095"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.3659,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.58320719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"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/T10454","display_name":"Optimal Power Flow Distribution","score":0.9998000264167786,"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/T10454","display_name":"Optimal Power Flow Distribution","score":0.9998000264167786,"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/T10223","display_name":"Microgrid Control and Optimization","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10603","display_name":"Smart Grid Energy Management","score":0.9983000159263611,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8239192962646484},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6624045968055725},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.45840883255004883},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.44360488653182983},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.4221947193145752},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.42192673683166504},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3979201316833496},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3434597849845886},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3080865442752838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29380878806114197},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2133501172065735},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1188511848449707}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8239192962646484},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6624045968055725},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.45840883255004883},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.44360488653182983},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.4221947193145752},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.42192673683166504},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3979201316833496},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3434597849845886},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3080865442752838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29380878806114197},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2133501172065735},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1188511848449707},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dtpi55838.2022.9998947","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dtpi55838.2022.9998947","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8899999856948853}],"awards":[{"id":"https://openalex.org/G2014663916","display_name":null,"funder_award_id":"2021ZD0112700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1987463767","https://openalex.org/W2141249818","https://openalex.org/W2153573511","https://openalex.org/W2463662408","https://openalex.org/W2513403950","https://openalex.org/W2516542501","https://openalex.org/W2588825664","https://openalex.org/W2781726626","https://openalex.org/W2901621510","https://openalex.org/W2904246096","https://openalex.org/W2963864421","https://openalex.org/W2964043796","https://openalex.org/W2966492573","https://openalex.org/W2991615077","https://openalex.org/W2991859550","https://openalex.org/W3042737196","https://openalex.org/W3122780823","https://openalex.org/W6684921986","https://openalex.org/W6692846177","https://openalex.org/W6747473740","https://openalex.org/W6757592117"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W2031695474","https://openalex.org/W2024136090","https://openalex.org/W2586732548","https://openalex.org/W4312713068","https://openalex.org/W3041490575","https://openalex.org/W2970690932"],"abstract_inverted_index":{"As":[0],"an":[1],"important":[2],"form":[3],"of":[4,46],"renewable":[5],"energy":[6],"integrated":[7],"to":[8,33,55,70,97,117],"the":[9,72,78,86,113,119,131],"power":[10],"system,":[11],"distribution":[12,47],"network":[13,21,38],"is":[14,53,105],"being":[15],"challenged":[16],"by":[17,82,107],"voltage":[18,35],"violation":[19,36],"and":[20,37,93,100,121],"loss":[22],"increase.":[23],"Currently,":[24],"model-based":[25,41],"Vol-Var":[26],"control":[27,89],"(VVC)":[28],"methods":[29,42],"are":[30,95],"widely":[31],"used":[32,96],"reduce":[34],"loss.":[39],"However,":[40],"need":[43],"accurate":[44,51],"parameters":[45],"network.":[48],"In":[49,57],"practice,":[50],"model":[52],"difficult":[54],"obtain.":[56],"this":[58],"paper,":[59],"we":[60],"propose":[61],"a":[62],"model-free":[63],"evolutionary":[64],"deep":[65],"reinforcement":[66],"learning":[67,88],"(E-DRL)":[68],"algorithm":[69],"solve":[71],"VVC":[73,103],"problem.":[74],"Based":[75],"on":[76,125],"E-DRL,":[77],"agent":[79],"evolves":[80],"autonomously":[81],"continuously":[83],"interacting":[84],"with":[85],"environment":[87],"strategy.":[90],"Inverter-based":[91],"PVs":[92],"SVGs":[94],"provide":[98],"fast":[99],"continuous":[101],"control.":[102],"problem":[104],"solved":[106],"soft":[108],"actor-critic":[109],"algorithm,":[110],"which":[111],"uses":[112],"maximum":[114],"entropy":[115],"technique":[116],"balance":[118],"exploration":[120],"exploitation.":[122],"Numerical":[123],"simulations":[124],"IEEE":[126],"13-bus":[127],"system":[128],"demonstrate":[129],"that":[130],"proposed":[132],"method":[133],"has":[134],"satisfied":[135],"performance.":[136]},"counts_by_year":[{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
