AGC of practical power system using backtracking search optimization algorithm

In this paper, backtracking search optimization algorithm (BSA) is proposed to solve automatic generation control (AGC) problem to achieve the best steady state and transient performances of power system. A practical two area multisource power system model is developed by considering different generating units (non-reheat, reheat and hydro) with different real time system parameters and non-linear security constraints such as governor dead band (GDB), generation rate constraint (GRC) and time delay (TD). BSA is used to tune the proportional integral derivative (PID) control parameters to improve the AGC performances considering all practical limitations. A new and innovative cost function is formulated considering area control error, stead state error, maximum overshoot, undershoot and number of peaks present in the output waveform with proper weight factors. The performance of the proposed method is compared with real coded genetic algorithm (RCGA) and particle swarm optimization (PSO) algorithm. Simulation results validate the better performance of BSA tuned PID control method compare to other two methods.