{"id":"https://openalex.org/W4404294841","doi":"https://doi.org/10.1109/idsta62194.2024.10747001","title":"Dynamic Threshold-Based Anomaly Detection in Photovoltaic Generation Time Series Using Statistical Methods","display_name":"Dynamic Threshold-Based Anomaly Detection in Photovoltaic Generation Time Series Using Statistical Methods","publication_year":2024,"publication_date":"2024-09-24","ids":{"openalex":"https://openalex.org/W4404294841","doi":"https://doi.org/10.1109/idsta62194.2024.10747001"},"language":"en","primary_location":{"id":"doi:10.1109/idsta62194.2024.10747001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idsta62194.2024.10747001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Fifth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)","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/A5109397643","display_name":"Michelle Melo Cavalcante","orcid":null},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Michelle Melo Cavalcante","raw_affiliation_strings":["University of Campinas (Unicamp),FEEC/LESF-MV,Campinas,Brazil"],"affiliations":[{"raw_affiliation_string":"University of Campinas (Unicamp),FEEC/LESF-MV,Campinas,Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072040219","display_name":"Jo\u00e3o Lucas de Souza Silva","orcid":"https://orcid.org/0000-0003-3206-2241"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jo\u00e3o Lucas de Souza Silva","raw_affiliation_strings":["University of Campinas (Unicamp),FEEC/LESF-MV,Campinas,Brazil"],"affiliations":[{"raw_affiliation_string":"University of Campinas (Unicamp),FEEC/LESF-MV,Campinas,Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018093654","display_name":"T\u00e1rcio Andr\u00e9 dos Santos Barros","orcid":"https://orcid.org/0000-0001-9413-1279"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"T\u00e1rcio Andr\u00e9 Dos Santos Barros","raw_affiliation_strings":["University of Campinas (Unicamp),FEEC/LESF-MV,Campinas,Brazil"],"affiliations":[{"raw_affiliation_string":"University of Campinas (Unicamp),FEEC/LESF-MV,Campinas,Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109397643"],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":null,"apc_paid":null,"fwci":0.7274,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77246772,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9695000052452087,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9695000052452087,"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":0.9225999712944031,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.9014999866485596,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/photovoltaic-system","display_name":"Photovoltaic system","score":0.7303745746612549},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6985841393470764},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6478484869003296},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5699964165687561},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5544009804725647},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5300124883651733},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3287087082862854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3226602077484131},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18710064888000488},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14881408214569092},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.12072226405143738},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10777923464775085},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0773555338382721}],"concepts":[{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.7303745746612549},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6985841393470764},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6478484869003296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5699964165687561},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5544009804725647},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5300124883651733},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3287087082862854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3226602077484131},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18710064888000488},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14881408214569092},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.12072226405143738},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10777923464775085},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0773555338382721},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idsta62194.2024.10747001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idsta62194.2024.10747001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Fifth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)","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":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2023290212","https://openalex.org/W2027714582","https://openalex.org/W2119760459","https://openalex.org/W2763133679","https://openalex.org/W2785664563","https://openalex.org/W2910274811","https://openalex.org/W2999785016","https://openalex.org/W3096657608","https://openalex.org/W3134784909","https://openalex.org/W3164929309","https://openalex.org/W3207583389","https://openalex.org/W4200048188","https://openalex.org/W4283802398","https://openalex.org/W4292289112","https://openalex.org/W4389051384","https://openalex.org/W4390767899","https://openalex.org/W4391422257","https://openalex.org/W4395681662"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"The":[0,71,109],"efficient":[1],"operation":[2],"of":[3,22,76,151],"photovoltaic":[4],"(PV)":[5],"plants":[6,132],"requires":[7],"continuous":[8],"monitoring":[9],"to":[10,40,90,119],"identify":[11,41,91,120],"and":[12,20,35,81,87,149],"correct":[13],"anomalies":[14],"that":[15],"may":[16],"affect":[17],"the":[18,23,38,100,124,134],"performance":[19],"lifespan":[21],"equipment.":[24],"However,":[25],"some":[26],"challenges":[27],"include":[28],"defining":[29],"which":[30,46],"data":[31,118,125],"can":[32,48],"be":[33,49],"collected":[34],"useful":[36],"from":[37],"installation":[39],"anomalies,":[42],"as":[43,45,97],"well":[44],"models":[47],"applied.":[50],"Therefore,":[51,139],"this":[52,140],"paper":[53],"proposes":[54],"an":[55,143],"approach":[56,141],"for":[57,136,146],"anomaly":[58],"detection":[59],"in":[60,130],"PV":[61,116,131,152],"generation":[62],"using":[63,114],"dynamic":[64],"threshold":[65],"techniques":[66],"based":[67],"on":[68],"descriptive":[69],"statistics.":[70],"methodology":[72],"involves":[73],"monthly":[74],"analysis":[75],"AC":[77,93],"power":[78,94],"characteristic":[79],"curves":[80],"irradiance":[82],"normalization,":[83],"applying":[84],"interquartile":[85],"ranges":[86],"standard":[88],"deviations":[89],"anomalies.":[92],"was":[95],"chosen":[96],"it":[98],"is":[99,112],"inverter":[101,117],"output":[102],"and,":[103],"therefore,":[104],"more":[105],"easily":[106],"obtained":[107],"data.":[108],"methodology\u2019s":[110],"implementation":[111],"validated":[113],"real":[115],"anomalous":[121],"behaviors.":[122],"Additionally,":[123],"used":[126],"are":[127],"generally":[128],"available":[129],"without":[133],"need":[135],"additional":[137],"sensors.":[138],"provides":[142],"effective":[144],"tool":[145],"predictive":[147],"maintenance":[148],"optimization":[150],"systems.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
