Title:Output Power Modeling of Wind Turbine Based on State Curve Analysis
Volume: 2
Author(s): Jiaying Huang, Wangqiang Niu*Xiaotong Wang
Affiliation:
- Key Laboratory of Transport Industry of Marine Technology and Control Engineering, Shanghai Maritime University,
Shanghai 201306, China
Keywords:
Wind turbine, power curve, state curve analysis, feature selection, operation condition, prediction.
Abstract:
Background: In wind power generation, the power curve can reflect the overall power
generation performance of a wind turbine. How to make the power curve have high precision and
be easy to interpret is a hot research topic.
Objective: Because the current power curve modeling method is not comprehensive in feature selection,
the simplified model and state curve of a wind turbine are introduced to avoid feature selection
and make the model interpret easily.
Methods: A power modeling method based on different working conditions is proposed. The
wind turbine system is simplified into three physical models of blades, mechanical transmission
and generator, and the energy transfer is expressed by mathematical expressions. The operation
process of the wind turbine is divided into three phases: Constant Power (CP), Constant Speed
(CS), and Maximum Power Point Tracking (MPPT), and the power expression of each phase is
given after the analysis of state curves.
Results: The effectiveness of the proposed method is verified by the Supervisory Control and
Data Acquisition (SCADA) data of a 2MW wind turbine. The experimental results show that the
Mean Absolute Percentage Error (MAPE) index of the proposed power modeling method based
on state curve analysis is 11.56%, which indicates that the power prediction result of this method
is better than that of the sixth-order polynomial regression method, whose MAPE is 13.88%.
Conclusion: The results show that the proposed method is feasible with high transparency and is
interpreted easily.