An Improved MGA for LFC in EV-Integrated Systems

Abstract

The study introduces the Improved Material Generation Algorithm (IMGA) for optimal tuning of a cascaded PDn–PI controller, aiming to enhance load frequency control (LFC) performance in a two-area interconnected power system with electric vehicle (EV) fleets. IMGA addresses issues of premature convergence in conventional algorithms by incorporating a Quadratic Interpolation Process (QIP), improving population diversity, convergence accuracy, and robustness. Evaluations under various operating conditions show that IMGA outperforms several optimizers, including PSO and QIO, with significant reductions in frequency deviations and tie-line power oscillations.