Abstract

There is a growing interest in using the flexibility of electric vehicles (EVs) to provide power system services, such as fast frequency regulation. Decentralized control is advocated due to its reliability and much lower communication requirements. A commonly used linear droop characteristic results in low average efficiencies, whereas controllers with 3 modes (idle, fully charging, fully discharging) result in large reserve errors when the aggregation size is small. To address these issues, we propose a stochastic, decentralized controller with tunable response granularity which minimizes switching actions. The EV fleet operator can optimize the chargers’ performance according to the fleet size, the service error requirements, the average switching rate and the average efficiency. We use real efficiency characteristics from EVs and chargers providing fast frequency regulation and we show that the proposed controller can significantly reduce reserve errors and increase efficiency for a given fleet size, while at the same time minimizing the switching actions."br

Abstract

The paper presents results of a study on the dynamic response of Electric Vehicle’s (EV) when participating in frequency control of an islanded system. The following cases were considered: when there is no EV performing frequency control, when the EV participates in primary frequency control and when the EV participates in both primary and secondary frequency control. Different parameters are tested in various combinations, and their influence on frequency deviation as well as power and energy provided by the EV with vehicle-to-grid (V2G) capability is shown."br/""br

Abstract

The provision of ancillary services is an additional revenue stream for the owners of inverter-equipped storage systems, such as batteries and electric vehicles. As real demonstrations have shown, primary frequency control (PFC) is a suitable and economically viable service for small-scale energy storage (ES) systems. This paper proposes a decentralized stochastic control policy, which significantly reduces ES units’ losses when providing PFC. The proposed controller can be tuned to obtain the desired service reserve provision errors, while achieving a balance between tracking accuracy and efficiency. An extension of the algorithm significantly reduces the switching rate of the devices by up to 95%. Analytical expressions for the reserve errors and the switching rates, dependent on the aggregation size and the controllers’ settings, are derived and verified by simulations. Simulation results show that the proposed controller can significantly reduce ES units’ losses when they are providing PFC by 8–15.5%, while achieving the expected tracking performance.