February 2018
Intermediate to advanced
280 pages
8h 42m
English
Content preview from Modeling and Modern Control of Wind Power
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Chapter 6Clustering-based Wind Turbine Generator Model Linearization
Haoran Zhao and Qiuwei Wu
Technical University of Denmark
In this chapter, a dynamic discrete time piecewise affine (PWA) model of a wind turbine is presented. This can be used for the advanced optimal control of a wind farm, in approaches such as model predictive control (MPC). In contrast to the partial linearization of the wind turbine model at selected operating points, the non-linearities of the wind turbine model are represented by a piecewise static function based on the wind turbine system inputs and state variables. The nonlinearity identification is based on a clustering-based algorithm, which combines clustering, linear identification, and pattern recognition techniques.
6.1 Introduction
Nowadays, the requirements for wind farm controllability specified by system operators have become more stringent, including active power control [1]. Different types of active power control have been specified, including absolute power limitation, delta limitation, and balance control. The modern wind farm is expected to operate like a conventional power plant, and be capable of tracking specific power references.
Due to the rapid development of power electronics, the controllability of modern wind turbines (WTs) has been much improved. According to the distribution algorithm of the wind farm control system, power references are assigned to each turbine. The role of individual wind turbines is as an actuator. Based ...
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