Multi-objective optimal provision of fast frequency response from EV clusters

Declining levels of rotational inertia in modern power systems prompt transmission system operators (TSOs) to develop novel ways of maintaining the balance between generation and demand. Services such as fast frequency response (FFR) can help the TSO achieve this balance. The growing penetration of electric vehicles (EVs) promotes the provision of FFR from clusters of EVs. Fast charging stations are more geared towards destination charging, whereas slow charging stations are more attractive as providers of FFR, given the longer connection times. In this study, the provision of FFR from EV clusters is formulated as a multi-objective optimisation problem with network security constraints and two minimisation objectives, i.e. the maximum frequency deviation following a disturbance and the energy provided by public EV charging stations. A methodology was developed to solve the optimisation problem with a variant of the non-dominated sorting genetic algorithm. This methodology allows the decision-maker to consider trade-offs among the objectives, leading to a more informed decision. An enhanced frequency-responsive aggregate model of an EV cluster was developed to study the provision of FFR in a multi-area power system. A reduced model of the Nordic power system was used to illustrate the performance of the proposed methodology.