Optimum Setting Strategy for WTGS by Using an Adaptive Neuro-Fuzzy Inference System

Yang Hu, Jizhen Liu, Zhongwei Lin

State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, P. R. China.

DOI: 10.4236/epe.2013.54B078                

Abstract

With the popularization of wind energy, the further reduction of power generation cost became the critical problem. As to improve the efficiency of control for variable speed Wind Turbine Generation System (WTGS), the data-driven Adaptive Neuro-Fuzzy Inference System (ANFIS) was used to establish a sensorless wind speed estimator. Moreover, based on the Supervisory Control and Data Acquisition (SCADA) System, the optimum setting strategy for the maximum energy capture was proposed for the practical operation process. Finally, the simulation was executed which suggested the effectiveness of the approaches.

Keywords

Wind Energy; Data Processing; Adaptive; Takagi-Sugeno (T-S) Fuzzy; Neuro-Network

Conflicts of Interest

The authors declare no conflicts of interest.

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