Control of a microgrid using robust data-driven-based controllers of distributed electric vehicles

Abstract

Current advancements in power electronic converters have paved a way to shift the attention from the traditional internal combustion engine to electric vehicles (EVs). In previous research works, the EVs are normally represented by an aggregate model or a first order transfer function, and they are mostly used for the frequency regulation in microgrids (MGs). These may not be valid assumptions since the EVs consist of various distributed units and power electronic converters. To make it more practical, distributed EV models with a function of MG voltage control should be further considered. This paper proposes an approach for MG voltage and frequency regulations using data-driven-based controllers for distributed EVs. Without requiring any MG parameters, information of uncertainties with respect to operation changes are monitored such that major stability indices, i.e., damping and robustness, can be automatically calculated. Considering these indices, the adaptive control technique is applied to design the controllers. The proposed adaptive data-driven-based controller is compared to a controller designed by considering dynamics of full-converter models. Simulation results are validated in a MG with renewable energy sources and distributed EVs under various operating points and uncertainties. • Mathematical modeling and investigation of a microgrid with distributed EVs, ESSs, SPVs, and wind generators. stability. • Robust control design of the data-driven-based controllers of distributed EVs using a mixed H 2 / H ∞ . • Considering performance of the proposed distributed controllers of EVs under various operations.