Robust Optimal Controller Design for Induction Generator Driven by Variable-Speed Wind Turbine with STATCOM Using Immune Algorithm

Abstract

this paper presents the modelling, controller design and a steady-state analysis algorithm for a wind-driven induction generator system. An output feedback linear quadratic controller is designed for the static synchronous compensator (STATCOM) and the variable blade pitch in a wind energy conversion system (WECS) in order to reach the voltage and mechanical power control under both grid-connection and islanding conditions. A two-reference-frame model is proposed to decouple the STATCOM real and reactive power control loops for the output feedback controller. To ensure zero steady-state voltage errors for the output feedback controller, the integrals of load bus voltage deviation and dc-capacitor voltage deviation are employed as the additional state variables. Pole-placement technique is used to determine a proper weighting matrix for the linear quadratic controller such that satisfactory damping characteristics can be achieved for the closed-loop system. Effects of various system disturbances on the dynamic performance have been simulated, and the results reveal that the proposed controller is effective in regulating the load voltage and stabilizing the generator rotating speed for the WECS either connected with or disconnected from the power grid. In addition, proper steady-state operating points for an isolated induction generator can be determined by the proposed steady-state analysis algorithm. Constant output frequency control using the derived steady-state characteristics of the isolated induction generator is then demonstrated in this paper.

Oscillatory Stability Prediction Using PSO Based Synchronizing and Damping Torque Coefficients

“…AI techniques utilize the logic and knowledge representations of expert systems, artificial neural network (ANN) [11]- [12] and evolutionary computation (EC). The EC field includes PSO [13]- [17], Evolutionary Programming (EP) [8], [18]- [19], Artificial Immune Systems (AIS) [20]- [22] and Firefly Algorithm (FA) [23]- [24]. In this study, EP, PSO and AIS were selected as optimization techniques.…”