Dynamic control of wind turbines |
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Authors: | Andrew Kusiak Wenyan Li Zhe Song |
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Affiliation: | aDepartment of Mechanical and Industrial Engineering, 3131 Seamans Center, The University of Iowa, Iowa City, IA 52242-1527, USA |
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Abstract: | The paper presents an intelligent wind turbine control system based on models integrating the following three approaches: data mining, model predictive control, and evolutionary computation. To enhance the control strategy of the intelligent system, a multi-objective model is proposed. The model involves five different objectives with different weights controlling the wind turbine performance. These weights are adjusted in response to the variable wind conditions and operational requirements. Three control factors, wind speed, turbulence intensity, and electricity demand are considered in eight computational scenarios. The performance of each scenario is illustrated with numerical results. |
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Keywords: | Wind turbine Wind energy Data mining Model predictive control Evolutionary computation algorithm Control strategy optimization |
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