Optimization of an adaptive droop control and powers allocation for a distributed generator under loads and grid uncertainties

Microgrids (MGs) provide a promising means of action to manage different distributed energy systems and energy consumers within required electrical limits and to participate in system services. To address these characteristics, this paper investigates an optimal control based on the optimization of powers allocation and adaptive fuzzy logic droop control for a MG based on a renewable distributed generator ensuring ancillary services. In fact, a sequential quadratic programming algorithm is used as an optimization function. The optimization strategy is successfully performed and mainly has two purposes. The first one is for the optimization of the powers coefficients to determine the required quantities of reactive and active powers to be absorbed or injected to the power grid, in order to ameliorate the levels of its frequency and voltage. The second purpose is the optimization of the membership-function parameters of the adaptive fuzzy logic droop controllers to compensate the powers to be exchanged with the power grid. In addition to the optimization task, the MG is managed by a power management algorithm based on the fuzzy logic technology. The strategy is developed and simulated using MATLAB/Simulink. The simulation results demonstrate the efficacity of the optimization method and the power management supervisor. Published by Elsevier Ltd.