{"id":"https://openalex.org/W4412762467","doi":"https://doi.org/10.1007/s44163-025-00451-1","title":"Resilient dispatching optimization of power system driven by deep reinforcement learning model","display_name":"Resilient dispatching optimization of power system driven by deep reinforcement learning model","publication_year":2025,"publication_date":"2025-07-30","ids":{"openalex":"https://openalex.org/W4412762467","doi":"https://doi.org/10.1007/s44163-025-00451-1"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00451-1","doi":"https://doi.org/10.1007/s44163-025-00451-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00451-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00451-1.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00451-1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100399673","display_name":"Haifeng Zhang","orcid":"https://orcid.org/0000-0002-7094-669X","observed_orcids":["https://orcid.org/0000-0002-7094-669X"]},"institutions":[{"id":"https://openalex.org/I4210138151","display_name":"Jilin Electric Power Research Institute (China)","ror":"https://ror.org/03pw0zs24","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210138151"]},{"id":"https://openalex.org/I4405272046","display_name":"State Grid Jilin Electric Power (China)","ror":"https://ror.org/03fsc3516","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405272046"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Zhang","raw_affiliation_strings":["State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China","institution_ids":["https://openalex.org/I4210138151","https://openalex.org/I4405272046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100703811","display_name":"Yifu Zhang","orcid":"https://orcid.org/0000-0002-4687-4016","observed_orcids":["https://orcid.org/0000-0002-4687-4016"]},"institutions":[{"id":"https://openalex.org/I4210138151","display_name":"Jilin Electric Power Research Institute (China)","ror":"https://ror.org/03pw0zs24","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210138151"]},{"id":"https://openalex.org/I4405272046","display_name":"State Grid Jilin Electric Power (China)","ror":"https://ror.org/03fsc3516","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405272046"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifu Zhang","raw_affiliation_strings":["State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China","institution_ids":["https://openalex.org/I4210138151","https://openalex.org/I4405272046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319572","display_name":"Jiajun Zhang","orcid":"https://orcid.org/0000-0001-5293-7434","observed_orcids":["https://orcid.org/0000-0001-5293-7434"]},"institutions":[{"id":"https://openalex.org/I4210138151","display_name":"Jilin Electric Power Research Institute (China)","ror":"https://ror.org/03pw0zs24","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210138151"]},{"id":"https://openalex.org/I4405272046","display_name":"State Grid Jilin Electric Power (China)","ror":"https://ror.org/03fsc3516","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405272046"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Zhang","raw_affiliation_strings":["State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China","institution_ids":["https://openalex.org/I4210138151","https://openalex.org/I4405272046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693146","display_name":"Xiangdong Meng","orcid":"https://orcid.org/0000-0002-6349-6205","observed_orcids":["https://orcid.org/0000-0002-6349-6205"]},"institutions":[{"id":"https://openalex.org/I4210138151","display_name":"Jilin Electric Power Research Institute (China)","ror":"https://ror.org/03pw0zs24","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210138151"]},{"id":"https://openalex.org/I4405272046","display_name":"State Grid Jilin Electric Power (China)","ror":"https://ror.org/03fsc3516","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405272046"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangdong Meng","raw_affiliation_strings":["State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Jilin Electric Power Research Institute, Changchun, 130021, Jilin, China","institution_ids":["https://openalex.org/I4210138151","https://openalex.org/I4405272046"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jiazu Sun","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiazu Sun","raw_affiliation_strings":["Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300074, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300074, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":{"value":1590,"currency":"USD","value_usd":1590},"apc_paid":{"value":1590,"currency":"USD","value_usd":1590},"fwci":5.088,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.96535121,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10424","display_name":"Electric Power System Optimization","score":0.9634000062942505,"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/T10424","display_name":"Electric Power System Optimization","score":0.9634000062942505,"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":0.00559999980032444,"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/T12451","display_name":"Smart Grid and Power Systems","score":0.005499999970197678,"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/power-system-dispatch","display_name":"power system dispatch","score":0.8529999852180481},{"id":"https://openalex.org/keywords/deep-reinforcement-learning","display_name":"deep reinforcement learning","score":0.9359999895095825},{"id":"https://openalex.org/keywords/load-distribution","display_name":"load distribution","score":0.9490000009536743},{"id":"https://openalex.org/keywords/power-supply-reliability","display_name":"power supply reliability","score":0.6399999856948853},{"id":"https://openalex.org/keywords/extreme-weather-events","display_name":"extreme weather events","score":0.7160000205039978},{"id":"https://openalex.org/keywords/power-system-restoration","display_name":"power system restoration","score":0.45399999618530273},{"id":"https://openalex.org/keywords/power-supply-restoration","display_name":"power supply restoration","score":0.609000027179718},{"id":"https://openalex.org/keywords/operational-cost-reduction","display_name":"operational cost reduction","score":0.6330000162124634},{"id":"https://openalex.org/keywords/real-time-scheduling","display_name":"real-time scheduling","score":0.4959999918937683},{"id":"https://openalex.org/keywords/power-system-stability","display_name":"power system stability","score":0.421999990940094}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8718029856681824},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6225671172142029},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.49780964851379395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48264938592910767},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4636005461215973},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2033187448978424},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"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":2,"locations":[{"id":"doi:10.1007/s44163-025-00451-1","doi":"https://doi.org/10.1007/s44163-025-00451-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00451-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00451-1.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7abc6bd0274a4da38e5113d4bbab9211","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/7abc6bd0274a4da38e5113d4bbab9211","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-27 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00451-1","doi":"https://doi.org/10.1007/s44163-025-00451-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00451-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00451-1.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9853000044822693,"id":"https://metadata.un.org/sdg/7"},{"display_name":"Industry, innovation and infrastructure","score":0.7207000255584717,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335967","display_name":"Science and Technology Project of State Grid","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412762467.pdf","grobid_xml":"https://content.openalex.org/works/W4412762467.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2093592737","https://openalex.org/W2794381367","https://openalex.org/W2953163185","https://openalex.org/W2991432219","https://openalex.org/W3122991923","https://openalex.org/W4293018786","https://openalex.org/W4313399219","https://openalex.org/W4313655082","https://openalex.org/W4362009354","https://openalex.org/W4378528210","https://openalex.org/W4385517009","https://openalex.org/W4385949022","https://openalex.org/W4386615382","https://openalex.org/W4389665209","https://openalex.org/W4390413862","https://openalex.org/W4390422113","https://openalex.org/W4390814438","https://openalex.org/W4391347706","https://openalex.org/W4391722755","https://openalex.org/W4393104303","https://openalex.org/W4397039333","https://openalex.org/W4399385695","https://openalex.org/W4399438724","https://openalex.org/W4399616476","https://openalex.org/W4399665988","https://openalex.org/W4399849565","https://openalex.org/W4400110068","https://openalex.org/W4401542311","https://openalex.org/W4401550616","https://openalex.org/W4403457568","https://openalex.org/W4403563311","https://openalex.org/W4404281908","https://openalex.org/W4404313325","https://openalex.org/W4404624427","https://openalex.org/W4406518179","https://openalex.org/W4406559583","https://openalex.org/W4406704044","https://openalex.org/W4408446761","https://openalex.org/W4410856015","https://openalex.org/W4411197050"],"related_works":["https://openalex.org/W4411321249","https://openalex.org/W7147541309","https://openalex.org/W4411398028","https://openalex.org/W7125939833","https://openalex.org/W7139945989","https://openalex.org/W4403023102","https://openalex.org/W4403085882","https://openalex.org/W7118121819","https://openalex.org/W4402659899","https://openalex.org/W4385741194"],"abstract_inverted_index":{"Power":[0],"systems":[1],"face":[2,252],"many":[3],"complex":[4,113],"and":[5,17,117,124,131,136,156,184,186,240,247,279,284,324,336,342],"severe":[6],"challenges":[7,59],"in":[8,69],"today's":[9],"power":[10,21,54,70,82,140,176,182,193,271,281,298,325,330,339,353],"sector.":[11],"Within":[12],"the":[13,15,20,26,30,34,36,49,53,64,139,148,158,163,168,175,179,188,192,202,216,235,251,255,270,294,307,317,321,329,334,348,352],"system,":[14,35,331],"stability":[16],"reliability":[18,327,337],"of":[19,29,39,52,121,138,191,198,253,297,328,338,351],"supply":[22,183,299,326],"are":[23],"affected":[24],"by":[25,222],"rapid":[27],"adjustment":[28],"energy":[31,245],"structure.":[32],"Outside":[33],"frequent":[37],"occurrence":[38],"extreme":[40],"weather":[41],"events":[42],"also":[43],"poses":[44],"a":[45,104,196,344],"considerable":[46],"threat":[47],"to":[48,102,128,233,262,273,276],"stable":[50,189,349],"operation":[51,142,190,278,350],"system.":[55,194,354],"To":[56],"address":[57],"these":[58],"effectively,":[60],"this":[61,76],"study":[62],"applies":[63],"deep":[65,149,203],"reinforcement":[66,150,204],"learning":[67,151,205],"model":[68,152,169,206,236,318],"system":[71,83,164,256,272,340],"elastic":[72],"scheduling":[73,84,214],"optimization.":[74],"In":[75,144,250,287],"study,":[77],"we":[78],"propose":[79],"an":[80,266],"innovative":[81],"strategy":[85],"based":[86],"on":[87],"Deep":[88],"Reinforcement":[89],"Learning":[90],"(DRL).":[91],"The":[92],"approach":[93],"combines":[94],"large-scale":[95],"historical":[96],"data":[97],"with":[98,211],"advanced":[99],"predictive":[100],"models":[101],"create":[103],"well-designed":[105],"decision-making":[106],"framework.":[107],"This":[108,229,268],"framework":[109],"can":[110,153,170],"simulate":[111],"various":[112],"working":[114],"conditions":[115,132],"online":[116],"realize":[118],"real-time":[119,134],"optimization":[120],"unit":[122,238],"combination":[123],"load":[125,241],"distribution":[126],"according":[127],"different":[129],"scenarios":[130],"through":[133],"monitoring":[135],"analysis":[137],"grid":[141],"status.":[143],"long-term":[145],"simulation":[146],"training,":[147],"continuously":[154],"learn":[155],"master":[157],"optimal":[159],"regulation":[160],"policy.":[161],"When":[162],"encounters":[165],"sudden":[166],"disturbances,":[167],"respond":[171],"quickly,":[172],"accurately":[173],"regulate":[174],"output,":[177],"maintain":[178],"balance":[180],"between":[181],"demand,":[185],"ensure":[187],"Through":[195],"series":[197],"rigorous":[199],"experimental":[200],"verifications,":[201],"shows":[207],"significant":[208],"advantages.":[209],"Compared":[210],"traditional":[212],"conventional":[213],"methods,":[215],"system's":[217],"operating":[218],"cost":[219],"is":[220,230,259,290,301],"reduced":[221,261],"at":[223],"least":[224],"10%":[225],"under":[226,306],"regular":[227,277],"operation.":[228],"mainly":[231],"due":[232],"optimizing":[234],"for":[237,347],"composition":[239],"distribution,":[242],"avoiding":[243],"unnecessary":[244],"waste":[246],"equipment":[248],"loss.":[249],"disruptions,":[254],"recovery":[257],"time":[258],"dramatically":[260,332],"less":[263],"than":[264],"half":[265],"hour.":[267],"allows":[269],"quickly":[274],"return":[275],"reduce":[280],"outages'":[282],"social":[283],"economic":[285],"impact.":[286],"particular,":[288],"it":[289],"worth":[291],"mentioning":[292],"that":[293,316],"success":[295],"rate":[296],"restoration":[300],"as":[302,304],"high":[303],"96%":[305],"simulated":[308],"central":[309],"natural":[310],"disaster":[311],"scenario,":[312],"which":[313],"fully":[314],"proves":[315],"significantly":[319],"improves":[320],"anti-interference":[322],"ability":[323],"enhances":[333],"efficiency":[335],"scheduling,":[341],"provides":[343],"strong":[345],"guarantee":[346]},"counts_by_year":[{"year":2026,"cited_by_count":24},{"year":2025,"cited_by_count":2}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2025-10-10T00:00:00"}