{"id":"https://openalex.org/W4407948447","doi":"https://doi.org/10.1109/cdc56724.2024.10886549","title":"Neural Spectral Clustering Based Voltage Area Partition of Active Distribution Systems","display_name":"Neural Spectral Clustering Based Voltage Area Partition of Active Distribution Systems","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W4407948447","doi":"https://doi.org/10.1109/cdc56724.2024.10886549"},"language":"en","primary_location":{"id":"doi:10.1109/cdc56724.2024.10886549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc56724.2024.10886549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 63rd Conference on Decision and Control (CDC)","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/A5101944241","display_name":"Shengyi Wang","orcid":"https://orcid.org/0000-0003-0117-040X"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shengyi Wang","raw_affiliation_strings":["Temple University,Department of Electrical and Computer Engineering,Philadelphia,USA"],"affiliations":[{"raw_affiliation_string":"Temple University,Department of Electrical and Computer Engineering,Philadelphia,USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016197750","display_name":"Liang Du","orcid":"https://orcid.org/0000-0002-3294-5071"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Du","raw_affiliation_strings":["Temple University,Department of Electrical and Computer Engineering,Philadelphia,USA"],"affiliations":[{"raw_affiliation_string":"Temple University,Department of Electrical and Computer Engineering,Philadelphia,USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lianren Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianren Zhu","raw_affiliation_strings":["Shanghai University,Department of Electrical Engineering,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai University,Department of Electrical Engineering,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042967962","display_name":"Yan Li","orcid":"https://orcid.org/0000-0003-4140-1911"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["The Pennsylvania State University,Department of Electrical Engineering,University Park,USA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University,Department of Electrical Engineering,University Park,USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101944241"],"corresponding_institution_ids":["https://openalex.org/I84392919"],"apc_list":null,"apc_paid":null,"fwci":0.1626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59834952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3495","last_page":"3500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14444","display_name":"Power Systems and Renewable Energy","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2102","display_name":"Energy Engineering and Power Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14444","display_name":"Power Systems and Renewable Energy","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2102","display_name":"Energy Engineering and Power Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12451","display_name":"Smart Grid and Power Systems","score":0.9861000180244446,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9767000079154968,"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/partition","display_name":"Partition (number theory)","score":0.708541750907898},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6619354486465454},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.58314448595047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3377434313297272},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32888656854629517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17980870604515076}],"concepts":[{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.708541750907898},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6619354486465454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.58314448595047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3377434313297272},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32888656854629517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17980870604515076},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc56724.2024.10886549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc56724.2024.10886549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 63rd Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.46000000834465027,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2593427583","https://openalex.org/W2784176971","https://openalex.org/W2913831476","https://openalex.org/W2973349269","https://openalex.org/W2984338059","https://openalex.org/W3020785977","https://openalex.org/W3034444391","https://openalex.org/W3128218652","https://openalex.org/W3152881947","https://openalex.org/W3157089210","https://openalex.org/W3174511347","https://openalex.org/W3190293619","https://openalex.org/W3201161517","https://openalex.org/W4312786192"],"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/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"As":[0],"distribution":[1,29,98],"systems":[2,30],"evolve":[3],"to":[4,75,88],"accommodate":[5],"large-scale":[6],"renewable":[7,67],"energy":[8],"sources,":[9],"maintaining":[10],"voltage":[11,23,41,49,78,94,127,144],"stability":[12],"becomes":[13],"increasingly":[14],"challenging.":[15],"Network":[16],"partitioning":[17,33],"plays":[18],"a":[19,90,104,113,121],"pivotal":[20],"role":[21],"in":[22,27,93,159],"control":[24,50],"tasks,":[25],"especially":[26],"active":[28],"(ADSs).":[31],"By":[32],"the":[34,62,72,136,141,150],"network":[35,114,142],"into":[36],"manageable":[37],"small":[38],"sub-networks,":[39],"i.e.,":[40],"area":[42],"partition":[43,115,140],"(VAP),":[44],"fine-grained,":[45],"decentralized,":[46],"and":[47,60,64,131],"coordinated":[48],"can":[51,139],"be":[52],"realized,":[53],"which":[54],"prevents":[55],"over-voltage":[56],"or":[57],"under-voltage":[58],"issues":[59],"facilitates":[61],"integration":[63],"absorption":[65],"of":[66,71,125,149],"energies.":[68],"However,":[69],"because":[70],"weak":[73],"ability":[74],"extract":[76],"complicated":[77],"relationships,":[79],"existing":[80],"naive":[81],"graph":[82],"clustering":[83,120,153],"VAP":[84,108],"methods":[85],"are":[86],"likely":[87],"suffer":[89],"performance":[91],"bottleneck":[92],"cohesiveness":[95,145],"for":[96,110],"large-sized":[97],"networks.":[99],"Therefore,":[100],"this":[101],"paper":[102],"proposes":[103],"neural":[105,122],"spectral":[106,123,152],"clustering-based":[107],"method":[109,138,154],"ADSs.":[111],"Specifically,":[112],"problem":[116],"is":[117],"solved":[118],"by":[119],"mapping":[124],"multi-phase":[126],"coupling":[128],"features.":[129],"Theoretical":[130],"experimental":[132],"results":[133],"show":[134],"that":[135,148],"proposed":[137],"with":[143],"higher":[146],"than":[147],"standard":[151],"while":[155],"bringing":[156],"certain":[157],"advantages":[158],"computational":[160],"efficiency.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}