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

Highlights

A model of wind power curve is developed from industrial data.

Wind power and speed data is clustered.

Support vector machine algorithm is applied to construct the model.

The model captures dynamic behavior of the wind turbine.

Computational results demonstrate effectiveness of the proposed approach.

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

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