A sensorless control for a variable speed wind turbine operating at partial load

Abstract

This paper presents a sensorless control for a variable speed wind turbine (WT) operating at partial load in order to eliminate the direct measurement of the wind speed. In this proposal, the estimated aerodynamic torque is used to determine the optimal reference of the speed control for maximum energy conversion. The maximization of the efficiency on energy conversion and the minimization of detrimental dynamical loads are control trade-offs considered in the design of an optimal discrete-time feedback LQG/LTR controller for the Wind Energy Conversion System (WECS), which is based on the optimization of a quadratic cost function. The performance of the proposed control when the WT is submitted to a gust or step variation on wind speed is evaluated from computational simulations. It is also presented some proposals for sensorless control of the electrical generator.

Influencia de las ráfagas de viento en la calidad de la energía de los parques eólicos

“…El cortocircuito en parques eólicos puede presentarse cuando una ráfaga de viento atraviesa el aerogenerador ocasionando inestabilidad y disminuyendo la confiabilidad del parque; las protecciones eléctricas juegan un rol importante en la estabilidad del sistema al realizar la desconexión del sistema eléctrico (Rocha, 2011).…”

Robust nonlinear control strategy to maximize energy capture in a variable speed wind turbine with an internal induction generator

“…The successive quadratic estimator (SQE) is selected as the optimum seeking algorithm. Although there are many optimization techniques in the literature [31][32][33], the advantage of this algorithm over conventional methods, such as the golden section search and simplex, is that no initial cost function values or bounds on the functional values are required [34]. The estimator approximates the cost function,P aero (ω(t)), as a quadratic function over a local bound and successively uses this property to predict the location of the optimum rotor speed, ω * .…”

“…After utilizing the fact that ω(t) ∈ L∞, from Assumption 6, it is apparent that f ( · ) ∈ L∞. After using Remarks 3 and 6 and the fact that e(t) ∈ L∞, along with (31), it can be shown that τ d (t) ∈ L∞. Remark 5 can be used along with the facts that…”

Control of Variable Speed Variable Pitch Wind Turbine at Above and Below Rated Wind Speed

“…In [12] fuzzy logic control has been proposed and the effective wind speed is estimated using sequential Monte Carlo simulator. Discrete time optimal LQR/LTR based on optimal quadratic function is studied in [13]. In [14] the effective wind speed is estimated by the frequency domain data fusion and the observer is formulated based on the mixed sensitivity problem with linear matrix Inequalities.…”