Smart Meter Insights: Identifying and Projecting Electric Vehicle Loads in Reykjavik

Time series data from 24,500 smart meters in the Greater Reykjavik Area (GRA) were analyzed to evaluate grid impacts in a high Electric Vehicle (EV) integration scenario. Features from Type 2 chargers were identified and used to classify meters likely servicing EVs. EV power consumption was integrated and annualized to compute EV equivalents behind each meter, estimated at 3 MWh/year for the average driver in Reykjavik. An data synthesizing algorithm was developed with a target EV per capita ratio of 0.6, corresponding to a 100% EV loading scenario. The algorithm synthesized a dataset corresponding to 85% EV loading scenario before populating data for all metered connections in the service area. Data was aggregated by secondary substations to identify transformer overloading under peak demand. This data-centered approach provided temporally- and geospatially- resolved insights, and can be adopted by other utilities with unlabeled smart meter data to prepare for future transport electrification.