Hybrid Genetic Algorithm Fuzzy-Based Control Schemes for Small Power System with High-Penetration Wind Farms

Abstract

Wind is a clean, abundant, and inexhaustible source of energy. However, wind power is not constant, as windmill output is proportional to the cube of wind speed. As a result, the generated power of wind turbine generators (WTGs) fluctuates significantly. Power fluctuation leads to frequency deviation and voltage flicker inside the system. This paper presents a new methodology for controlling system frequency and power. Two decentralized fuzzy logic-based control schemes with a high-penetration non-storage wind–diesel system are studied. First, one is implemented in the governor of conventional generators to damp frequency oscillation, while the other is applied to control the pitch angle system of wind turbines to smooth wind output power fluctuations and enhance the power system performance. A genetic algorithm (GA) is employed to tune and optimize the membership function parameters of the fuzzy logic controllers to obtain optimal performance. The effectiveness of the suggested controllers is validated by time domain simulation for the standard IEEE nine-bus three-generator test system, including three wind farms. The robustness of the power system is checked under normal and faulty operating conditions.