Journal article
Predictive model of yaw error in a wind turbine
Energy (Oxford), Vol.123, pp.119-130
03/15/2017
DOI: 10.1016/j.energy.2017.01.150
Abstract
The yaw position of a wind turbine is adjusted in response to the changing wind direction for maximum energy extraction. A data-mining approach is proposed to predict wind direction. To accommodate the full range of yaw motion, the wind direction data is transformed into two time series (sine value and cosine values). Parameters of the time series are selected for predictive modeling. Four data-mining algorithms are applied to build prediction models. Industrial data is used to develop, validate, and test the proposed models. Computational experience with data representing four seasons and four sampling frequencies is reported in this paper.
•A new model for prediction of wind direction needed for yaw control in a wind turbine is developed.•A new approach for transformation of wind measurements is proposed to produce feasible predicted values.•Comparative analysis of different data-mining algorithms is performed.•The prediction model developed in the paper is applied to yaw control of a wind turbine.•Characteristics of wind directions at different seasons are analyzed.
Details
- Title: Subtitle
- Predictive model of yaw error in a wind turbine
- Creators
- Tinghui Ouyang - University of IowaAndrew Kusiak - University of IowaYusen He - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Energy (Oxford), Vol.123, pp.119-130
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.energy.2017.01.150
- ISSN
- 0360-5442
- eISSN
- 1873-6785
- Language
- English
- Date published
- 03/15/2017
- Academic Unit
- Industrial and Systems Engineering; Nursing
- Record Identifier
- 9984187075002771
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