Disturbance Observer and Tube-Based Model Predictive Controlled Electric Vehicles for Frequency Regulation of an Isolated Power Grid

Abstract

This paper presents a frequency regulation approach applied to a renewable penetrated isolated power grid in the presence of a large number of Electric Vehicles (EVs). A disturbance observer is initially designed for a reduced-order model of the system to produce a supplementary frequency control signal for the aggregated EVs. The reduced order model is obtained by combining the variations in the load, wind, photovoltaic systems, and aggregated EVs in order to yield a lumped disturbance to be estimated by the proposed disturbance observer. A tube-based Model Predictive Control (MPC) is then proposed to provide efficient control signals for improving the response of the aggregated EVs. The control signals are produced so as to obtain the least value of frequency deviation error with a minimum control effort while taking a variety of operational and physical constraints into consideration. The proposed control strategy offers the capability to cope with the uncertainties caused by the external disturbances by coordinating the charging and discharging of aggregated EVs. The impact of the delay in communication links is also investigated by conducting a stability analysis to obtain the delay margin. Simulations are conducted on an isolated system to illustrate the effectiveness of the designed observer, and also to examine the advantage of the presented tube-based MPC over a conventional MPC, a fuzzy proportional-integral control, and a linear quadratic regulator control.