This paper presents a planning and control strategy to manage the provision of ancillary services with aggregates of electric vehicles (EVs). The study is inspired by recent directives from the Italian Regulatory Authority for Energy, Networks and Environment (ARERA), which opens the way for the participation of new actors in the ancillary services market, including EV aggregates. On a day-ahead basis, the charging point operator computes its total EV power baseline and upward/downward bids for the next day, by solving a dynamic scheduling problem, based on a vehicle-by-vehicle assessment of the next day’s charging demand. Then, in real time, a model predictive controller manages the EV charging sessions to track the baseline and to respond to possible upward/downward regulation signals from the TSO. This two-level approach allows to fulfill the day-ahead obligations (the agreed baseline and regulation bids) and to provide efficient charging service to the EV users, also in presence of deviations of the actual demand from the day ahead forecast. Simulation results validate the approach on realistic scenarios in line with the ARERA resolution 300/17, and show that demand-based ancillary services paradigm is feasible, if supported by a flexible recharging planning and control system. • Electric vehicles aggregates participation in the ancillary services market. • Joint day-ahead planning and real time control of binding services. • Assessment of service technical feasibility in relation to electric vehicles flexibility margins. • A bidding strategy based on a vehicle-by-vehicle representation of charging demand. • A multi-player model predictive control application.
Giorgio et al. (Sun,) studied this question.