Since the energy generation capacity of installed wind turbine is increasing, the interest in optimising the efficiency of these wind turbines is growing, as well. The optimal operating points for the power and speed control of the turbines depends on a mapping to the power conversion ratio from tip speed ratio and blade pitch angles. This mapping usually is not known in analytical form, but in general represented by approximated two–dimensional maps (i.e. look–up tables). Another issue can derive from the accuracy of the map itself. It might be correct but uncertain. The main problem of the methods available in the literature is that the power conversion ratio is represented as two–dimensional map. Therefore, this paper suggests a scheme to estimate this power conversion ratio in an analytical form, described as two–dimensional polynomial, whose degree has to be optimised as well. This estimated analytical relation can subsequently be used to design optimal controller, as well as for robust fault diagnosis applications.

Estimation of the Power Coefficient Map for a Wind Turbine System

SIMANI, Silvio;
2011

Abstract

Since the energy generation capacity of installed wind turbine is increasing, the interest in optimising the efficiency of these wind turbines is growing, as well. The optimal operating points for the power and speed control of the turbines depends on a mapping to the power conversion ratio from tip speed ratio and blade pitch angles. This mapping usually is not known in analytical form, but in general represented by approximated two–dimensional maps (i.e. look–up tables). Another issue can derive from the accuracy of the map itself. It might be correct but uncertain. The main problem of the methods available in the literature is that the power conversion ratio is represented as two–dimensional map. Therefore, this paper suggests a scheme to estimate this power conversion ratio in an analytical form, described as two–dimensional polynomial, whose degree has to be optimised as well. This estimated analytical relation can subsequently be used to design optimal controller, as well as for robust fault diagnosis applications.
2011
Power coefficient identification; polynomial method; linear identification algorithm; least–square method; wind turbine benchmark.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1616466
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