A Proposed Metaheuristic Proportional-Integral-Derivative Optimization Approach for Frequency Stability in Renewable Energy– Based Microgrids

This study addresses load frequency control (LFC) in a hybrid microgrid to mitigate frequency fluctuations induced by renewable energy integration. The proportional-integral-derivative (PID) controller was employed, and its gains were optimized using genetic algorithm (GA), particle swarm optimization, and, for the first time, the starfish optimization algorithm (SFOA). A novel multi-criteria objective function was introduced by combining the conventional integral of time multiplied absolute error metric with frequency deviation and settling time, ensuring a more comprehensive performance evaluation. The results demonstrate the superior performance of the SFOA-based PID controller. Specifically, SFOA achieved the shortest settling time of 0.14 seconds, the lowest total cost function value of 0.075, and the lowest undershoot of −0.0789. Both graphical and numerical analyses confirmed its more effective suppression of frequency oscillations and reduced amplitude in system dynamics. Overall, this study presents the first application of SFOA in microgrid LFC and highlights that the proposed objective function significantly improves both transient and steady-state behaviors, offering a robust and reliable solution for future smart grid scenarios.

Cite this article as: S. Çelikdemir, A. Elegel and D. Öztürk, “A proposed metaheuristic proportional-integral-derivative optimization approach for frequency stability in renewable energy–based microgrids,” Electrica, 2026, 26, 0311. doi: 10.5152/electrica.2026.25311.