New perspectives on maximum wind energy extraction of variable-speed wind turbines using previewed wind speeds. (15th February 2020)

• Record Type: Journal Article
• Authors: Song, Dongran; Yang, Yinggang; Zheng, Songyue; Deng, Xiaofei; Yang, Jian; Su, Mei; Tang, Weiyi; Yang, Xuebing; Huang, Lingxiang; Joo, Young Hoon
• Is Part Of: Energy conversion and management. Volume 206(2020)
• Publication Date: 2020-02-15
• Subjects: Wind turbine -- Maximum wind energy extraction -- Previewed wind -- Nonlinear predictive control; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2020.112496
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: Maximum wind energy extraction formulated. Potential solution of generator torque sequence set predefined. Efficient search algorithm to set out the optimization problem. Validation on two wind turbine models with different scales. More than 1% of increased energy extraction efficiency. Abstract: Maximum wind energy extraction remains a challenge for the large-scale wind turbines due to their increasing moment of inertia. In this study, a novel nonlinear predictive control method using previewed wind speeds is proposed to address the issue of maximum wind energy extraction for variable-speed wind turbines. Different from the conventional structure, the proposed nonlinear predictive control is based on the discrete prediction model established by a large time step. By doing so, the number of time discrete points is significantly reduced and the quantity of the solution set becomes numerable. As a result, the implementation complexity and computational burden are able to be relieved, and the real-time implementation becomes practical and easy to carry out. The proposed method is demonstrated on two models of wind turbines with different scales, and its performance is compared with the industrial controller. Comparison results show that the increased energy extraction efficiency gained by the proposed method is more than 1% on the two turbine models under different wind conditions, and thus the superior capability in extracting wind energy promises potential industrial applications. Meanwhile, the expense is the considerable increment of torque variation, which can be relieved by revising the control parameters. The presented method provides new insights into the design of the control methods for wind turbines equipped with advanced measurement devices.