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Distributed fractional-order PID control of multi-area interconnected power systems by population based extremal optimization

How to design an effective and efficient load-frequency controller (LFC) for a multi-area interconnected power system to improve its power quality is a challenging issue. In order to deal with this issue, this paper presents a novel distributed fractional-order PID (DFOPID) control method for the load-frequency control of each area by using an adaptive population-based extremal optimization (APEO) algorithm. The basic idea behind the proposed method is formulating the optimal design issue of DFOPID controller as a typical constrained optimization problem by minimizing the weighted sum of area control errors and the control signal subjecting to some pre-specified tolerances firstly, and then solving this problem by using APEO algorithm. The simulation results on a two-area interconnected power system with matched and mismatched system parameters have shown that the proposed method is superior to reported genetic algorithm, particle swarm optimization and chaotic NSGA-II algorithm based fractional-order LFC methods in terms of dynamic response and robustness.