Control of voltage and frequency based on uncertainty analysis using Bayesian method and effective power flow control of storage role in electrical vehicle charging station. (December 2022) - Rajamand, Sahbasadat; Caglar, Ramazan
Abstract: In new microgrids, electrical vehicles (EVs) are increasingly used for less green-house gases production and renewable distributed generators (RDGs) are mainly employed for load supporting. In view of control of the main parameters as voltage and frequency, the existence of RDGs and EVs causes low inertial property and thus, frequency/voltage may be degraded when sudden load change occurs in the system. On the other hand, EV charging station (EVCS) can effectively compensate the low-inertial status with energy reservation and power flow control in the system. However, some challenges such as energy supporting of all EVs, control of power flow from/to EVCS and the control of frequency/voltage in all parts of the system must be considered. Moreover, the uncertainties of RDGs, EVs, EVCS and load demand must be assumed for frequency/voltage control strategy. In this paper, the main purpose is providing an efficient control structure to achieve more stable frequency/voltage regulation. For this goal, uncertainty modeling is done using Bayesian method (BM) combined with point estimation method (PEM) to compensate the uncertainty effect of RDGs, EVs and loads. In addition, feedback signal of EVCS and main control loop are employed in the proposed control structure for more stable frequency and voltage regulation. The test microgrid is implemented in MATLAB while the simulation is done using the Sim-power toolbox. Simulation results show interesting enhancement in frequency/voltage stability and power/voltage profile of the proposed microgrid using the proposed method.