Modeling wind-turbine power curve: A data partitioning and mining approach

Tinghui Ouyang, Andrew Kusiak and Yusen He

Renewable Energy, 2017, vol. 102, issue PA, 1-8

Abstract: Model of a power curve allows to analyze performance of a wind turbine and compare it with other turbines. An approach based on centers of data partitions and data mining is proposed to construct such a model. Wind speed range is partitioned into intervals for which centers are computed. The centers are regarded as representative samples in modeling. A support vector machine algorithm is used to build a power curve model. Computational results have demonstrated that the model reflects dynamic properties of a power curve. In addition it is accurate and efficient to generate. The model accuracy has been tested with industrial wind energy data.

Keywords: Wind turbine power curve; Partition centers; Data mining; Support vector machine (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (32)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:102:y:2017:i:pa:p:1-8

DOI: 10.1016/j.renene.2016.10.032

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