{"id":"https://openalex.org/W2759010591","doi":"https://doi.org/10.1109/isgt.2017.8086037","title":"A study on probability of distribution loads based on expectation maximization algorithm","display_name":"A study on probability of distribution loads based on expectation maximization algorithm","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2759010591","doi":"https://doi.org/10.1109/isgt.2017.8086037","mag":"2759010591"},"language":"en","primary_location":{"id":"doi:10.1109/isgt.2017.8086037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt.2017.8086037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://eprints.nottingham.ac.uk/44837/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015836560","display_name":"Amin Ganjavi","orcid":null},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Amin Ganjavi","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105472148","display_name":"Edward Christopher","orcid":null},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Edward Christopher","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009745214","display_name":"C. Mark Johnson","orcid":"https://orcid.org/0000-0002-7546-0453"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"C. Mark Johnson","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068454145","display_name":"John Clare","orcid":"https://orcid.org/0000-0001-8243-4280"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jon Clare","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142263535"],"apc_list":null,"apc_paid":null,"fwci":0.7038,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.72843418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"39","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9797000288963318,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9797000288963318,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9571999907493591,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9538000226020813,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.7564754486083984},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.7252795696258545},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6553297638893127},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6251513957977295},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5570181012153625},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5482240319252014},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5434116125106812},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4853281080722809},{"id":"https://openalex.org/keywords/mixture-distribution","display_name":"Mixture distribution","score":0.4623018801212311},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4526316225528717},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.4143944978713989},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.39746028184890747},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35585469007492065},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29626062512397766},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27407729625701904},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.24813437461853027},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1659708321094513},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11429077386856079}],"concepts":[{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.7564754486083984},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.7252795696258545},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6553297638893127},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6251513957977295},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5570181012153625},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5482240319252014},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5434116125106812},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4853281080722809},{"id":"https://openalex.org/C56672385","wikidata":"https://www.wikidata.org/wiki/Q17157111","display_name":"Mixture distribution","level":3,"score":0.4623018801212311},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4526316225528717},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4143944978713989},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.39746028184890747},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35585469007492065},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29626062512397766},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27407729625701904},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.24813437461853027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1659708321094513},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11429077386856079},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace 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":3,"locations":[{"id":"doi:10.1109/isgt.2017.8086037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt.2017.8086037","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.nottingham.ac.uk:44837","is_oa":true,"landing_page_url":"http://eprints.nottingham.ac.uk/44837/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196364","display_name":"Nottingham ePrints (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"pmh:oai:nottingham-repository.worktribe.com:890985","is_oa":true,"landing_page_url":"https://nottingham-repository.worktribe.com/output/890985","pdf_url":null,"source":{"id":"https://openalex.org/S4306402483","display_name":"Repository@Nottingham (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Presentation / Conference Contribution"}],"best_oa_location":{"id":"pmh:oai:eprints.nottingham.ac.uk:44837","is_oa":true,"landing_page_url":"http://eprints.nottingham.ac.uk/44837/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196364","display_name":"Nottingham ePrints (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1486632395","https://openalex.org/W1882650697","https://openalex.org/W1967460951","https://openalex.org/W1981367467","https://openalex.org/W2049633694","https://openalex.org/W2088587780","https://openalex.org/W2108288396","https://openalex.org/W2108876167","https://openalex.org/W2134199473","https://openalex.org/W2141840627","https://openalex.org/W2144268297","https://openalex.org/W2145455389","https://openalex.org/W2155405335","https://openalex.org/W2157410673","https://openalex.org/W2162851697","https://openalex.org/W2186512298","https://openalex.org/W2332441433","https://openalex.org/W2567948266","https://openalex.org/W3143528639","https://openalex.org/W6628849183","https://openalex.org/W6676085441","https://openalex.org/W6686523984"],"related_works":["https://openalex.org/W2198732287","https://openalex.org/W4287816759","https://openalex.org/W2803473765","https://openalex.org/W2372918136","https://openalex.org/W2153481672","https://openalex.org/W2105786884","https://openalex.org/W2128540811","https://openalex.org/W4312864369","https://openalex.org/W1658960529","https://openalex.org/W4293056332"],"abstract_inverted_index":{"In":[0],"a":[1,30,51,66,101],"distribution":[2,115],"power":[3],"network,":[4],"the":[5,109],"load":[6,60,85,106,116,129],"model":[7,54],"has":[8,46],"no":[9],"certain":[10],"pattern":[11],"or":[12],"predicted":[13],"behaviour":[14],"due":[15],"to":[16,62,103],"large":[17,79],"range":[18],"of":[19,59,68,74,111,114,120,131,137],"data":[20,81,86,107,130],"and":[21,87],"changes":[22],"in":[23],"energy":[24],"consumption":[25],"for":[26,78,117,135],"end-user":[27],"consumers.":[28],"Thus,":[29],"powerful":[31,52],"analysis":[32],"based":[33],"on":[34],"probabilistic":[35,105],"structure":[36],"is":[37,50,76,125],"required.":[38],"For":[39],"this":[40],"paper":[41,99],"Gaussian":[42,70],"Mixture":[43],"Model":[44],"(GMM)":[45],"been":[47],"used.":[48],"GMM":[49,75],"probability":[53],"that":[55],"allows":[56],"different":[57],"types":[58],"distributions":[61],"be":[63,91],"presented":[64],"as":[65,83],"combination":[67],"several":[69],"distributions.":[71],"The":[72,122],"parameters":[73,89],"unknown":[77],"random":[80],"such":[82],"real":[84],"these":[88],"can":[90],"identified":[92],"by":[93],"Expectation":[94],"Maximization":[95],"(EM)":[96],"algorithm.":[97],"This":[98],"presents":[100],"method":[102,124],"evaluate":[104],"concerning":[108],"time-evolution":[110],"any":[112,118],"type":[113],"duration":[119,136],"time.":[121],"proposed":[123],"explained":[126],"through":[127],"generated":[128],"100":[132],"residential":[133],"houses":[134],"one":[138],"year.":[139]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}