Load frequency control of interconnected power system using artificial intelligent techniques based fractional order PIλ Dµ controller

This paper presents an algorithm for load frequency control of multi-area power system. A more realistic models is used to represent the elements of power system. The frequency bias factor (B) is set optimally. The effect of generation rate constraints (GRC) and the dead band characteristics of the governor is taken into consideration. A simultaneous optimization of the fractional order (PIλ Dµ) control parameters, the speed regulation (R) of the governor and the frequency bias factor (B) is proposed for the first time. The objective function to be minimizes is a modified integral time absolute error (MITAE). The tuning of the control parameters is based on using cuckoo search algorithm (CSA) to minimize the objective function. The proposed algorithm is applied to a typical interconnected three-area power systems with a different levels of load step change. Results of simulation of the presented method are compared with those obtained by applying particle swarm optimization technique. The results obtained reveal the robustness of the suggested algorithm in terms of settling time and peak over shoot.