{"id":"https://openalex.org/W7130744694","doi":"https://doi.org/10.1109/vppc66000.2025.11392871","title":"Predicting EV Recharges from the Point of View of Charging Hub Managers","display_name":"Predicting EV Recharges from the Point of View of Charging Hub Managers","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W7130744694","doi":"https://doi.org/10.1109/vppc66000.2025.11392871"},"language":"en","primary_location":{"id":"doi:10.1109/vppc66000.2025.11392871","doi":"https://doi.org/10.1109/vppc66000.2025.11392871","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vppc66000.2025.11392871","pdf_url":null,"source":{"id":"https://openalex.org/S4363608327","display_name":"IEEE Vehicle Power and Propulsion Conference (VPPC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Vehicle Power and Propulsion Conference (VPPC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5111891671","display_name":"Federico Rios","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Federico Rios","raw_affiliation_strings":["Politecnico di Milano,Electrical Engineering Division,Department of Energy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Electrical Engineering Division,Department of Energy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032843072","display_name":"Cristian Giovanni Colombo","orcid":"https://orcid.org/0000-0002-3382-9910","observed_orcids":["https://orcid.org/0000-0002-3382-9910"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Cristian Giovanni Colombo","raw_affiliation_strings":["Politecnico di Milano,Electrical Engineering Division,Department of Energy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Electrical Engineering Division,Department of Energy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074047579","display_name":"Michela Longo","orcid":"https://orcid.org/0000-0002-3780-4980","observed_orcids":["https://orcid.org/0000-0002-3780-4980"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michela Longo","raw_affiliation_strings":["Politecnico di Milano,Electrical Engineering Division,Department of Energy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Electrical Engineering Division,Department of Energy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062787426","display_name":"Dario Zaninelli","orcid":"https://orcid.org/0000-0002-9837-3096","observed_orcids":["https://orcid.org/0000-0002-9837-3096"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Dario Zaninelli","raw_affiliation_strings":["Politecnico di Milano,Electrical Engineering Division,Department of Energy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Electrical Engineering Division,Department of Energy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027017319","display_name":"Sonia Leva","orcid":"https://orcid.org/0000-0002-7883-0034","observed_orcids":["https://orcid.org/0000-0002-7883-0034"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sonia Leva","raw_affiliation_strings":["Politecnico di Milano,Electrical Engineering Division,Department of Energy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Electrical Engineering Division,Department of Energy","institution_ids":["https://openalex.org/I93860229"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I93860229"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.65020931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9990000128746033,"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/T10768","display_name":"Electric Vehicles and Infrastructure","score":0.9990000128746033,"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":0.00039999998989515007,"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/T10603","display_name":"Smart Grid Energy Management","score":9.999999747378752e-05,"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/electric-vehicle-charging","display_name":"electric vehicle charging","score":0.9810000061988831},{"id":"https://openalex.org/keywords/neural-time-series","display_name":"neural time series","score":0.6919999718666077},{"id":"https://openalex.org/keywords/overfitting","display_name":"overfitting","score":0.5329999923706055},{"id":"https://openalex.org/keywords/battery-capacity","display_name":"battery capacity","score":0.4560000002384186},{"id":"https://openalex.org/keywords/state-of-charge","display_name":"state of charge","score":0.9869999885559082},{"id":"https://openalex.org/keywords/load-forecasting","display_name":"load forecasting","score":0.6190000176429749}],"concepts":[{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6064000129699707},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6017000079154968},{"id":"https://openalex.org/C2777767291","wikidata":"https://www.wikidata.org/wiki/Q1080291","display_name":"Sizing","level":2,"score":0.5997999906539917},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.5701000094413757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5501999855041504},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5462999939918518},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.44510000944137573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43309998512268066},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38659998774528503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37139999866485596},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3400999903678894},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C2776582896","wikidata":"https://www.wikidata.org/wiki/Q5368536","display_name":"State of charge","level":4,"score":0.3034999966621399},{"id":"https://openalex.org/C22762622","wikidata":"https://www.wikidata.org/wiki/Q628904","display_name":"Operating point","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.26930001378059387},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.25870001316070557},{"id":"https://openalex.org/C2779859299","wikidata":"https://www.wikidata.org/wiki/Q7602527","display_name":"Start point","level":3,"score":0.25859999656677246},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2565000057220459},{"id":"https://openalex.org/C174091901","wikidata":"https://www.wikidata.org/wiki/Q2670986","display_name":"Groundwater recharge","level":4,"score":0.25519999861717224},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.2531999945640564}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vppc66000.2025.11392871","doi":"https://doi.org/10.1109/vppc66000.2025.11392871","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vppc66000.2025.11392871","pdf_url":null,"source":{"id":"https://openalex.org/S4363608327","display_name":"IEEE Vehicle Power and Propulsion Conference (VPPC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Vehicle Power and Propulsion Conference (VPPC)","raw_type":"proceedings-article"},{"id":"pmh:oai:re.public.polimi.it:11311/1307308","doi":null,"is_oa":false,"landing_page_url":"https://hdl.handle.net/11311/1307308","pdf_url":null,"source":{"id":"https://openalex.org/S4306400312","display_name":"Virtual Community of Pathological Anatomy (University of Castilla La Mancha)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79189158","host_organization_name":"University of Castilla-La Mancha","host_organization_lineage":["https://openalex.org/I79189158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8485000133514404,"display_name":"Affordable and clean energy"},{"id":"https://metadata.un.org/sdg/9","score":0.6773999929428101,"display_name":"Industry, innovation and infrastructure"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"short-term":[1],"forecasts":[2],"of":[3,61,68,89,132,143],"the":[4,37,52,57,86,98,110,125,129,141],"power":[5],"drawn":[6],"by":[7],"individual":[8],"EVs":[9],"charging":[10,19,71],"sessions":[11],"are":[12,82],"critical":[13],"for":[14,36],"sizing":[15],"and":[16,76],"operating":[17],"public":[18],"hubs,":[20],"yet":[21],"hub":[22],"managers":[23],"seldom":[24],"know":[25],"battery":[26,148],"capacity,":[27],"initial":[28],"State":[29],"Of":[30],"Charge":[31],"(SOC)":[32],"or":[33,113,150,152],"charging-algorithm":[34],"details":[35],"vehicles":[38],"they":[39],"serve.":[40],"This":[41],"paper":[42],"explores":[43],"how":[44],"much":[45],"predictive":[46],"skill":[47],"can":[48],"be":[49],"extracted":[50],"when":[51],"only":[53],"information":[54,126],"available":[55],"is":[56,73],"historical":[58],"power-time":[59],"profile":[60],"past":[62],"sessions.":[63],"A":[64],"real-world":[65],"data":[66],"set":[67,112],"719":[69],"209":[70],"events":[72],"cleaned,":[74],"filtered":[75],"analysed.":[77],"Several":[78],"neural":[79],"time-series":[80],"architectures":[81],"trained":[83],"to":[84,120,156],"predict":[85],"second":[87],"half":[88],"a":[90],"recharge":[91],"event":[92],"from":[93,128],"its":[94],"first":[95],"half,":[96],"with":[97],"best":[99],"performer":[100],"scoring":[101],"41":[102],"Symmetric":[103],"Mean":[104],"Absolute":[105],"Percentage":[106],"Error":[107],"(SMAPE).":[108],"Scaling":[109],"training":[111],"deliberately":[114],"over-fitting":[115],"on":[116],"single-user":[117],"subsets":[118],"fails":[119],"improve":[121],"accuracy,":[122],"indicating":[123],"that":[124],"missing":[127],"operator\u2019s":[130],"point":[131],"view":[133],"fundamentally":[134],"constrains":[135],"forecastability.":[136],"The":[137],"results":[138],"therefore":[139],"motivate":[140],"integration":[142],"lightweight":[144],"EV":[145],"metadata":[146],"(e.g.,":[147],"size":[149],"state-of-charge)":[151],"external":[153],"contextual":[154],"signals":[155],"unlock":[157],"higher-fidelity":[158],"power-demand":[159],"forecasting.":[160]},"counts_by_year":[],"updated_date":"2026-10-06T10:28:23.643775","created_date":"2026-02-21T00:00:00"}