Symbiotic organisms search algorithm for automatic generation control of interconnected power systems including wind farms

Abstract

Automatic generation control (AGC) plays an important role in power systems, where it maintains the system frequency and tie-line power flow at their desired values. This study presents a novel symbiotic organisms search (SOS) algorithm in order to optimally design the proportional–integral–derivative (PID) controllers in the AGC of interconnected multiple-area power systems including wind farms uncertainty and system non-linearity. The PID controllers’ parameters define the design variables of the optimisation problem. The SOS algorithm is applied to different objective functions such as integral square error and integral absolute of error. The efficacy of the proposed controller is compared with other competing evolutionary algorithms-based proportional–integral or PID controller. The system performance is evaluated under different operating conditions such as different loading, variation of system parameters, and an addition of wind energy uncertainty. For obtaining realistic responses, real wind speed data that extracted from Zafarana location in Egypt is used in this study. The validity of the proposed controller is extensively confirmed using the simulation results. With the SOS-based PID controllers, the dynamic responses for the AGC of interconnected power systems, including wind farms uncertainty can be further enhanced.