Whale Optimization Algorithm‐Based Adaptive Controller for Grid‐Following Inverters: Conceptualization, Simulation, and Experimental Validation

ABSTRACT Grid‐tied inverters are widely used to integrate renewable energy sources into the electrical grid. In these systems, LCL filters are often utilized as the interface between the inverter and the grid. However, LCL filters present a resonance peak that may turn the system unstable. In addition, as the grid weakens, lower is the frequency of this peak, posing relevant challenges for the control system. In this sense, adaptive controllers emerge as feasible solutions once they can adjust their gains in response to any perturbation. However, the design of an adaptive controller requires plenty of experience due to the high quantity of parameters. This work proposes a systematic parametrization for a robust model reference adaptive proportional integral controller using the whale optimization algorithm, considering controller performance and stability constraints. The optimized controller is applied on a grid‐tied inverter with an LCL filter. Simulation results indicate the feasibility of using the proposed automatic procedure to design the controller, obtaining fast current tracking and high robustness to unmodeled dynamics and exogenous disturbances. In addition, significant parametric variations (more than 30 times the nominal value of grid inductance) are imposed during the experiment to evaluate the robustness of the optimized controller, which is able to maintain the closed‐loop globally stable and properly controlled even in the face of all adversities. Processor‐in‐the loop experiments are presented to validate the feasibility and satisfactory performance of the optimized controller. Experimental results are provided to prove the controller's feasibility in real‐world application, demonstrating that grid‐injected currents comply with the IEEE 1547 standard.