Regulation of WTG Dynamic Response to Parameter Variations of Analytic Wind Stochasticity

Endusa Billy Muhando, University of the Ryukyus

Abstract

Although variable-speed operation can reduce the impact of transient wind gusts and subsequent component fatigue, this is still an unknown factor that must now be quantified. Reduction in drive-train stresses caused by fatigue loads in high wind turbulence is fundamental to realizing both output power levelling and long service life for a wind turbine generator (WTG). This paper presents an evolutionary controller comprising a linear quadratic Gaussian (LQG) and neurocontroller (NC) acting in tandem to effect optimal performance under high turbulence intensities. The control objectives are maximum energy conversion and reduction in mechanical stresses on the system components. The proposed paradigm utilizes generator torque in controlling the rotor speed in relation to the highly turbulent wind speed, thereby ensuring the extracted aerodynamic power is maintained at a constant value, while shaft moments are regulated. The performance of the proposed controller is compared with that of the LQG and it is found that the former is more efficient in maintaining rated power, minimizing shaft torque variations, and shows robustness to parameter variations.