Enhancement of a Small Power System Performance Using Multi-Objective Optimization

Abstract

Optimal multi-objective design of proportional-integral-derivative controller parameters for a small power system using epsilon multi-objective genetic algorithm ( $\varepsilon $ -MOGA) has been presented in this paper. The small power system includes a wind turbine generator (WTG), a diesel generator, a battery energy storage system (BESS), and a load. The proposed scheme is applied for controlling the pitch angle system of the WTG to minimize the wind turbine mechanical blades stress, reduce the wind output power deviation, control the system frequency, and decrease the size of BESS by regulating its charging level. The deviations of input wind power are considered in a frequency domain. The low-frequency component is reduced by the pitch angle control system of WTG, while the high-frequency component is mitigated by the charge/discharge of the BESS, respectively. The input of the pitch angle control system of WTG is determined according to the low-frequency component of the input wind power deviation and the BESS state of charge. The output power of BESS is determined according to its state of charge, the high-frequency component of the input wind power deviation, and the frequency deviations. The effectiveness of the proposed controller is confirmed by numerical simulations.