Optimization of AGC parameters in interconnected power systems using enhanced marine predators algorithm

Abstract

In this work, an objective function considering performance indices and an enhanced marine predator algorithm ( EMP A ) are proposed to optimize the parameters of a Fuzzy - PID controller for Automatic Generation Control of interconnected power systems. Ini- tially, a two-area non-reheat unit was implemented, and the gains of five different controllers were adjusted to verify the suitability of MP A employing IT AE objective function in solving AGC issues. The superiority of the proposed MP A based F - P ID controller has been demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as water cycle algorithm ( W CA ) based F - P ID controller for the same interconnected power system. EMP A - F - P ID method which integrates EMP A and F - P ID controller is tested in a typical two-area non-reheat system, and sys- tem responses reflect the advantages of the proposed objective function and EMP A . Then, sensitivity analysis is carried out to identify the closed-loop system’s robustness. A two-area non-reheat unit was also tested under the generation rate constraints ( GRC ) nonlinearity. To guarantee the suitability of the proposed MP A - F - P ID , a model with a mixture of power plants, such as reheat, hydro, and gas units, in each area was carried out with and without the HV DC link, which can increase practical issues with AGC . The proposed controller’s robustness was studied for all models under numerous scenarios, including step load perturbations ( SLP ). Simulation results proved that the proposed MP A - F - P ID provided superior performance compared to recently reported techniques in terms of peaks and settling time.