An effective method based on simulated annealing for automatic generation control of power systems

Abstract

In this study, a novel hybrid Simulated Annealing-Genetic Algorithm (hSA-GA) is proposed. In the hSA-GA, population-based SA is used and each solution in the population is improved using the local search operator. The information exchange between the improved solutions is provided by the crossover operator. A new selection operator is used to ensure the balance between intensification and diversification. The hSA-GA is tested first on nine benchmark functions. Then it is used for tuning proportional–integral–derivative (PID) parameters for automatic generation control (AGC) of multi-area interconnected power systems. Firstly, PID parameters are determined with hSA-GA on a two-area interconnected non-reheating thermal system (System-1) in two different generator time constants. Secondly, to demonstrate the effect of supplementary control in AGC systems, the system is simulated with hSA-GA tuned PID controller and without controller. Additionally, the performance of the proposed hSA-GA is observed on AGC system of two area thermal power system with governor dead-band (GDB) nonlinearity (System-2). Transient responses of Δf1, Δf2 and ΔPtie obtained for both System-1 and System-2 are compared with studies on the same systems in the literature and it is seen that hSA-GA exhibits better control performance on power systems than compared studies. The proposed algorithm shows the best performance in System-1 (when Tg=0.08). Accordingly, settling times of Δf1, Δf2 and ΔPtie are reduced to 2.33 s, 3.783 s and 3.11 s, respectively. Finally, the non-linear two area thermal power system is tested with a load varying between ±50% for 180 s to validation of proposed algorithm and results are compared relevant studies.