COORDINATING HOUSEHOLD DEMAND AND VEHICLE-USE ARCHETYPES TO ENABLE URBAN ON-STREET EV CHARGING WITHOUT DISTRIBUTION UPGRADES
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Abstract
Urban electrification strategies are increasingly relying on on-street charging to support residents without private driveways. However, distribution networks in dense neighbourhoods often operate near the limits established during their initial planning. This paper uses Kensington, London, as an example to focus on on-street charging in medium-density urban areas with terraced housing, and to investigate whether coordinated, phase-aware charging can increase EV uptake in multi-occupancy residential settings without triggering costly network reinforcement. Specifically, the study quantifies the impact of household demand stochasticity and vehicle-use heterogeneity on available thermal headroom and charging adequacy, as defined by standard After Diversity Maximum Demand (ADMD) planning levels. The analysis integrates a high-resolution residential demand model with behavioural EV driving archetypes to simulate overnight charging over a 365-day period, utilising the existing grid connection of six flat terraced houses without grid updates. The model employs ADMD to define aggregate feeder capacity and to simulate scenarios in which total load is managed to prevent exceeding the per-household diversified rating. The framework evaluates the sufficiency of the morning state of charge (SoC) for one, two or three vehicles by comparing an optimised phase-balancing strategy with a worst-case uncoordinated allocation. The results demonstrate that, for a six-flat terraced house, the available “soft” ADMD headroom, which is dictated by the coincidence of household base load, is the primary binding constraint rather than charger nameplate power. For initial uptake of one EV per six flats, the mean morning battery SoC remains high (70–73%). However, as the number of vehicles increases to three per shared constraint, the system reaches a capacity-saturated regime. In this state, optimisation improves grid quality and prevents localised phase overloads, but cannot offset the overall energy deficit. These findings suggest that, although phase-aware coordination can facilitate early-stage on-street electrification, saturation levels will require either physical reinforcement or advanced demand flexibility.
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smart EV charging, on-street charging access inequality, after-diversity maximum demand (ADMD), three-phase phase balancing, EV charging control
Anadón Martínez, V., & Sumper, A. (2023). Planning and operation objectives of public electric vehicle charging infrastructures: A review. Energies, 16(14), 5431.
Barteczko-Hibbert, C. (2015). After Diversity Maximum Demand (ADMD) Report (CLNR-L217; p. 24). Northern Powergrid (Northeast) Limited. http://www.networkrevolution.co.uk/project-library/diversity-maximum-demand-admd-report/
Doda, D. K., Beemkumar, N., Awasthi, A., & Gautam, A. K. (2024). Electric Vehicle Energy Management: Charging in Sustainable Urban Settings for Smart Cities. 540, 02022.
Energy Networks Association. (2019). Engineering Recommendation P2/7—Security of Supply (Engineering Recommendation P2; Version 7). Energy Networks Association. https://www.dcode.org.uk/assets/files/Qualifying%20Standards/ENA_EREC_P2_Issue%207_(2019).pdf
European Commision. (2025). REPowerEU - 3 years on. https://energy.ec.europa.eu/topics/markets-and-consumers/actions-and-measures-energy-prices/repowereu-3-years_en
International Electrotechnical Commission. (2017). IEC 61851-1:2017 Electric vehicle conductive charging system—Part 1: General requirements (61851; Version 1:2017). International Electrotechnical Commission. https://webstore.iec.ch/en/publication/33644
Ivanova, A., Chassin, D., Aguado, J., Crawford, C., & Djilali, N. (2020). Techno‐economic feasibility of a photovoltaic‐equipped plug‐in electric vehicle public parking lot with coordinated charging. IET Energy Systems Integration, 2(3), 261–272.
Office for Zero Emission Vehicles. (2025). Apply for the electric vehicle (EV) pavement channels grant. GOV.UK. https://www.gov.uk/guidance/apply-for-the-electric-vehicle-ev-pavement-channels-grant
Regulation (EU) 2021/1119 of the European Parliament and of the Council of 30 June 2021 Establishing the Framework for Achieving Climate Neutrality and Amending Regulations (EC) No 401/2009 and (EU) 2018/1999 (‘European Climate Law’), 2021/1119, European Parliament (2021). https://eur-lex.europa.eu/eli/reg/2021/1119/oj/eng
Rubenis, A., & Laizans, A. (2026). Residential electricity demand structure in multi-apartment buildings: Implications for rooftop photovoltaic availability and urban energy resilience. Baltic Journal of Economic Studies, 12(2). https://doi.org/10.30525/2256-0742/2025-11-5-126-138
Rubenis, A., Laizans, A., & Aleksans, G. (2025). (Pre-print) The Cost of Access: Economic Inequality in On-Street Electric Vehicle Charging in Riga and London. International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, 25.
Rubenis, A., Tonova, J., & Morozovs, V. (2025). Modelling Operational Archetypes for Corporate Fleet Electrification. Baltic Journal of Economic Studies, 11(5), 126–138. https://doi.org/10.30525/2256-0742/2025-11-5-126-138
Sastry, K. V., Taylor, D. G., & Leamy, M. J. (2023). Decentralized smart charging of electric vehicles in residential settings: Algorithms and predicted grid impact. IEEE Transactions on Smart Grid, 15(2), 1926–1938.
Schofield, J. R., Carmichael, R., Tindemans, S., Bilton, M., Woolf, M., & Strbac, G. (2015). Low carbon london project: Data from the dynamic time-of-use electricity pricing trial, 2013. uK Data Service, SN, 7857(2015), 7857–7851.
Teawnarong, A., Angaphiwatchawal, P., & Chaitusaney, S. (2024). Optimal operations of local energy market with electric vehicle charging and incentives for local grid services. IEEE Access.
Tveit, M. H., Sevdari, K., Marinelli, M., & Calearo, L. (2022). Behind-the-meter residential electric vehicle smart charging strategies: Danish cases. 1, 1–5.
Ubitricity. (2025). AC Lamppost Chargers. Ubitricity. https://ubitricity.com/en/charging-solutions/ac-lamppost/
UK Power Networks. (2014). SmartMeter Energy Consumption Data in London Households [Csv]. London Datastore. https://data.london.gov.uk/dataset/smartmeter-energy-consumption-data-in-london-households-vqm0d
UK Power Networks. (2025a). BNO Guide An overview of multi-occupied buildings and Building Network Operators (BNOs) (V4). UK Power Networks. https://media.umbraco.io/ukpn-cms/fj5i0udr/uk-power-networks-bno-guide-2025.pdf
UK Power Networks. (2025b). EDS 08-2101 LV Customer Supplies up to 100A (ENGINEERING DESIGN STANDARD EDS 08-2101; Version 14). https://g81.ukpowernetworks.co.uk/library/design-and-planning/lv/eds-08-2101-lv-customer-supplies-up-to-100a
Ye, Z., Li, T., & Low, S. (2022). Towards balanced three-phase charging: Phase optimization in adaptive charging networks. Electric Power Systems Research, 212, 108322. https://doi.org/10.1016/j.epsr.2022.108322
Zhang, G., Tan, S. T., & Wang, G. G. (2017). Real-time smart charging of electric vehicles for demand charge reduction at non-residential sites. IEEE Transactions on Smart Grid, 9(5), 4027–4037.
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