Modern Control Methods for Adaptive Droop Coefficients’ Design

TLDR: This chapter presents a novel droop controller design method that involves fuzzy logic-based adaptive p − ω droop coefficient design and model reference- based adaptive q − v droop coefficients design that facilitates the controller to adaptively respond according to the disturbances and thereby provides effective closed-loop control actions to improve the transient response of the system.

Abstract: The microgrid controller comprises of cascaded “droop–voltage–current” control modules. The voltage and current controllers are basically proportional plus integral (PI)-type control logics. So, the efficacy of these controllers depends on the accuracy of the PI gain parameter tuning. Besides, the droop control logic supplies the reference voltage required for voltage control and the voltage control logic supplies the reference current required for the current control. Therefore, the total control operation depends on the effective design of droop control logic, which depends on the design of droop coefficients and their adaptivity to respond with respect to a disturbance. There are many conventional methods available as mentioned in the literature; however, to meet the modern power system requirements, these conventional methods have to be updated with features such as adaptivity, disturbance rejection, capability to address inertia related issues. With this intent, this chapter provides modern control methods for adaptive droop coefficients’ design. In brief, this chapter presents a novel droop controller design method that involves fuzzy logic-based adaptive p − ω droop coefficient design and model reference-based adaptive q − v droop coefficient design. This method facilitates the controller to adaptively respond according to the disturbances and thereby provides effective closed-loop control actions to improve the transient response of the system. The comparisons with the conventional methods are presented with the help of simulation and experimental results to persuade the importance of the proposed adaptive droop control method.