STABILITY IMPROVEMENT OF SUPERCONDUCTING GENERATORS USING ARTIFICIAL INTELLIGENCE-BASED STATIC VAR COMPENSATOR

Document Type : Original Article

Author

Electrical Engineering Dept., Faculty of Engineering, Minoufiya University

Abstract

In this paper, superconducting generator (SCG) stability enhancement via coordinated design of a governor controller (GC) and a static VAR compensator (SVC)-based fuzzy logic stabilizer is investigated. The GC is a conventional lead stabilizer activated by the speed error signal, while the signal produced by the SVC-based stabilizer is based on the SCG speed deviation and acceleration, and on two fuzzy membership functions reflecting few simple control rules. An objective function is defined and the design problem of efficient GC and SVC-based fuzzy stabilizer is formulated as an optimization problem. Particle swarm optimization (PSO) technique is employed to search for optimal parameters of GC and SVC-based stabilizer. Simulation results show that the proposed PSO-tuned control scheme provides good damping to the SCG, and enhances its stability over a range of operating conditions.

Keywords