{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T21:29:05Z","timestamp":1772054945792,"version":"3.50.1"},"reference-count":28,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T00:00:00Z","timestamp":1756857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"national funds through FCT\u2014Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia, I.P.","award":["UID\/50014\/2023"],"award-info":[{"award-number":["UID\/50014\/2023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Energies"],"abstract":"<jats:p>As electric vehicle (EV) adoption accelerates, residential buildings\u2014particularly multi-dwelling structures\u2014face increasing challenges to electrical infrastructure, notably due to conservative sizing practices of electrical feeders based on maximum simultaneous demand. Current sizing methods assume all EVs charge simultaneously at maximum capacity, resulting in unnecessarily oversized and costly electrical installations. This study proposes an optimized methodology to estimate accurate coincidence factors, leveraging simulations of EV user charging behaviors in multi-dwelling residential environments. Charging scenarios considering different fleet sizes (1 to 70 EVs) were simulated under two distinct premises of charging: minimization of current allocation to achieve the desired battery state-of-charge and maximization of instantaneous power delivery. Results demonstrate significant deviations from conventional assumptions, with estimated coincidence factors decreasing non-linearly as fleet size increases. Specifically, applying the derived coincidence factors can reduce feeder section requirements by up to 86%, substantially lowering material costs. A fuzzy logic inference model is further developed to refine these estimates based on fleet characteristics and optimization preferences, providing a practical tool for infrastructure planners. The results were compared against other studies and real-life data. Finally, the proposed methodology thus contributes to more efficient, cost-effective design strategies for EV charging infrastructures in residential buildings.<\/jats:p>","DOI":"10.3390\/en18174679","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T12:07:32Z","timestamp":1756901252000},"page":"4679","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Fuzzy Logic Estimation of Coincidence Factors for EV Fleet Charging Infrastructure Planning in Residential Buildings"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4708-4526","authenticated-orcid":false,"given":"Salvador","family":"Carvalhosa","sequence":"first","affiliation":[{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, Centre for Power and Energy Systems, s\/n R. Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, s\/n R. Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6950-1714","authenticated-orcid":false,"given":"Jos\u00e9 Rui","family":"Ferreira","sequence":"additional","affiliation":[{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, Centre for Power and Energy Systems, s\/n R. Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, s\/n R. Dr. Roberto Frias, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7866-9068","authenticated-orcid":false,"given":"Rui Esteves","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, Centre for Power and Energy Systems, s\/n R. Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, s\/n R. Dr. Roberto Frias, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,3]]},"reference":[{"key":"ref_1","unstructured":"(2000). Dire\u00e7\u00e3o Geral da Energia Parte 5\/Sec\u00e7\u00e3o 51. Regras T\u00e9cnicas de Instala\u00e7\u00f5es El\u00e9ctricas de Baixa Tens\u00e3o, Imprensa Nacional-Casa da Monedal."},{"key":"ref_2","unstructured":"(2023). National Fire Protection Association Section 220. National Electrical Code, IEEE."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Jonas, T., Daniels, N., and Macht, G. (2023). Electric Vehicle User Behavior: An Analysis of Charging Station Utilization in Canada. Energies, 16.","DOI":"10.3390\/en16041592"},{"key":"ref_4","unstructured":"Rastad, A.A., Busengdal, H.S., and Hiep, E. (2023). Report on Consumer Behaviour, European Comission."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Almaghrebi, A., James, K., Al Juheshi, F., and Alahmad, M. (2024). Insights into Household Electric Vehicle Charging Behavior: Analysis and Predictive Modeling. Energies, 17.","DOI":"10.3390\/en17040925"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Unterluggauer, T., Hipolito, F., Klyapovskiy, S., and Andersen, P.B. (2022). Impact of Electric Vehicle Charging Synchronization on the Urban Medium Voltage Power Distribution Network of Frederiksberg. World Electr. Veh. J., 13.","DOI":"10.3390\/wevj13100182"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ramsebner, J., Hiesl, A., and Haas, R. (2020). Efficient Load Management for BEV Charging Infrastructure in Multi-Apartment Buildings. Energies, 13.","DOI":"10.3390\/en13225927"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"796","DOI":"10.3390\/smartcities6020038","article-title":"Car-Sharing Systems in Smart Cities: A Review of the Most Important Issues Related to the Functioning of the Systems in Light of the Scientific Research","volume":"6","year":"2023","journal-title":"Smart Cities"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"102231","DOI":"10.1016\/j.trd.2020.102231","article-title":"Siting Charging Stations for Electric Vehicle Adoption in Shared Autonomous Fleets","volume":"80","author":"Lokhandwala","year":"2020","journal-title":"Transp. Res. D Transp. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1186\/s12544-022-00560-3","article-title":"Survey of Charging Management and Infrastructure Planning for Electrified Demand-Responsive Transport Systems: Methodologies and Recent Developments","volume":"14","author":"Ma","year":"2022","journal-title":"Eur. Transp. Res. Rev."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"104265","DOI":"10.1016\/j.scs.2022.104265","article-title":"Integration of Charging Behavior into Infrastructure Planning and Management of Electric Vehicles: A Systematic Review and Framework","volume":"88","author":"Patil","year":"2023","journal-title":"Sustain. Cities Soc."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kumar, M., Panda, K.P., Naayagi, R.T., Thakur, R., and Panda, G. (2023). Comprehensive Review of Electric Vehicle Technology and Its Impacts: Detailed Investigation of Charging Infrastructure, Power Management, and Control Techniques. Appl. Sci., 13.","DOI":"10.3390\/app13158919"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Hong, S.-K., Lee, S.G., and Kim, M. (2020). Assessment and Mitigation of Electric Vehicle Charging Demand Impact to Transformer Aging for an Apartment Complex. Energies, 13.","DOI":"10.3390\/en13102571"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Quiros-Tortos, J., Ochoa, L.F., and Lees, B. (2015, January 5\u20137). A Statistical Analysis of EV Charging Behavior in the UK. Proceedings of the 2015 IEEE PES Innovative Smart Grid Technologies Latin America (ISGT LATAM), Montevideo, Uruguay.","DOI":"10.1109\/ISGT-LA.2015.7381196"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1109\/TTE.2019.2921854","article-title":"Grid Loading Due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behavior","volume":"5","author":"Calearo","year":"2019","journal-title":"IEEE Trans. Transp. Electrif."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.epsr.2018.09.022","article-title":"Statistical Characterisation of the Real Transaction Data Gathered from Electric Vehicle Charging Stations","volume":"166","author":"Flammini","year":"2019","journal-title":"Electr. Power Syst. Res."},{"key":"ref_17","unstructured":"Aunedi, M., Woolf, M., Strbac, G., Babalola, O., and Clark, M. (2015, January 16\u201318). Characteristic Demand Profiles of Residential and Commercial EV Users and Opportunities for Smart Charging. Proceedings of the Internation Conference on Electricity Distribution (CIRED), Lyon, France."},{"key":"ref_18","unstructured":"Tong, X., Guo, C., Yang, X., and Chen, C. (2016, January 25\u201328). Research on Characteristics of Electric Vehicle Charging Load and Distribution Network Supportability. Proceedings of the 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), Xi\u2019an, China."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Thie, N., Junge, E., Hillenbrand, S., and Konermann, M. (2019, January 3\u20136). Evaluation of Grid Compatible Load Management Concepts for E-Mobility in Distribution Grids. Proceedings of the 2019 54th International Universities Power Engineering Conference (UPEC), Bucharest, Romania.","DOI":"10.1109\/UPEC.2019.8893580"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Palomino, A., and Parvania, M. (2018, January 9\u201311). Probabilistic Impact Analysis of Residential Electric Vehicle Charging on Distribution Transformers. Proceedings of the 2018 North American Power Symposium (NAPS), Fargo, ND, USA.","DOI":"10.1109\/NAPS.2018.8600630"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1109\/TTE.2021.3088275","article-title":"Coincidence Factors for Domestic EV Charging from Driving and Plug-In Behavior","volume":"8","author":"Bollerslev","year":"2022","journal-title":"IEEE Trans. Transp. Electrif."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Huaman-Rivera, A., Calloquispe-Huallpa, R., Luna Hernandez, A.C., and Irizarry-Rivera, A. (2024). An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies. Electronics, 13.","DOI":"10.3390\/electronics13122259"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"166537","DOI":"10.1109\/ACCESS.2024.3491379","article-title":"Electric Vehicle Charging Method for Existing Residential Condominiums","volume":"12","author":"Carvalhosa","year":"2024","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"102637","DOI":"10.1016\/j.trc.2020.102637","article-title":"A Data Driven Typology of Electric Vehicle User Types and Charging Sessions","volume":"115","author":"Helmus","year":"2020","journal-title":"Transp. Res. Part. C Emerg. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Berg, K., and L\u00f6schenbrand, M. (2023). Data Set of a Norwegian Energy Community. Mendeley Data.","DOI":"10.1016\/j.dib.2021.107683"},{"key":"ref_26","unstructured":"Opstad, A., Bakken, B.H., Doorman, G., Nygard, H.S., and Sevdari, K. (2024). CSE N\u00b035 December 2024, CIGRE."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"114291","DOI":"10.1109\/ACCESS.2023.3322278","article-title":"Modeling of Electric Vehicle Charging Demand and Coincidence of Large-Scale Charging Loads in Different Charging Locations","volume":"11","author":"Jokinen","year":"2023","journal-title":"IEEE Access"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"101581","DOI":"10.1016\/j.segan.2024.101581","article-title":"Impact of Electric Vehicle Charging Simultaneity Factor on the Hosting Capacity of LV Feeder","volume":"40","author":"Fani","year":"2024","journal-title":"Sustain. Energy Grids Netw."}],"container-title":["Energies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1996-1073\/18\/17\/4679\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:38:39Z","timestamp":1760035119000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1996-1073\/18\/17\/4679"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,3]]},"references-count":28,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["en18174679"],"URL":"https:\/\/doi.org\/10.3390\/en18174679","relation":{},"ISSN":["1996-1073"],"issn-type":[{"value":"1996-1073","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,3]]}}}