Wind-turbine collective-pitch control via a fuzzy predictive algorithm

Ahmed Lasheen and Abdel Latif Elshafei

Renewable Energy, 2016, vol. 87, issue P1, 298-306

Abstract: This paper proposes a new fuzzy predictive algorithm for collective pitch control of large wind turbines. Collective pitch controllers operate in region three to harvest the rated power and maintain the rated speed. The wind turbine model is represented by a Takagi–Sugeno (T–S) fuzzy model. The number of T–S fuzzy rules is reduced based on a gap – metric criterion. A model predictive controller is designed based on the fuzzy model taking into consideration the pitch actuator constraints. The proposed controller is coupled with conventional PI controllers for individual pitch control so as to minimize the moments on the turbine blades. A Kalman observer is designed to estimate the immeasurable states. The performance of the proposed fuzzy-predictive controller is compared to a gain schedule PI controller and a mixed H2/H∞ controller. Simulation results, based on a typical 5-MW offshore wind turbine, demonstrate the superiority of the proposed fuzzy-predictive controller.

Keywords: Wind turbines; Collective pitch control; Predictive control; T–S fuzzy models (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:87:y:2016:i:p1:p:298-306

DOI: 10.1016/j.renene.2015.10.030

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