Optimal Coordination of Local Flexibility from Electric Vehicles with Social Impact Consideration

We implement a customised AC Optimal Power Flow (AC OPF) formulation which integrates into the optimisation an indicator reflecting the social impact of flexibility from EV users, based on the analysis of historical EV charging behaviours. The contribution of EV owners to reducing wind curtailment is optimised to enhance the acceptability of flexibility procurement, as the method targets EV users whose charging habits are most likely to align with flexibility requirements. Our method integrates social, technological, and economic perspectives with optimal flexibility coordination, and utilises clustering of EVs through a k-means algorithm. To ensure scalability, we introduce a polar coordinate-based dimension reduction technique. The flexibility optimisation approach is demonstrated on the Orkney grid model, incorporating demand and wind farm generation data, as well as multi-year charging data from 106 EVs. Results indicate that, by building upon the existing habits of EV users, curtailment can be reduced by 96.7% during a typical summer week, when curtailment can be most prevalent. This research demonstrates a foundational and transferable approach which is cognisant of social-techno-economic factors towards accelerating decarbonisation and tackling the stochastic challenges of new demand and generation patterns on local distribution networks.