Power Curve Modelling for Wind Turbine Using Artificial Intelligence Tools and Pre-established Inference Criteria

Journal of Modern Power Systems and Clean Energy

Aida A. Ferreira¹  Jonata C. de Albuquerque²  Otoni Nobrega Neto²  Ronaldo R. B. de Aquino²  Milde M. S. Lira²  Manoel Afonso de Carvalho² 

[1] Federal Institute of Pernambuco,DASE,Recife,Brazil;Federal University of Pernambuco,Department of Electrical Engineering,Recife,Brazil;

关键词: Wind turbine;    pre-training;    artificial intelligence;    artificial neural network (ANN);    fuzzy inference system (FIS);   

DOI  :  10.35833/MPCE.2019.000236

来源: DOAJ

【 摘 要 】

We propose a new way to develop non-parametric models of power curves using artificial intelligence tools. One parametric model and eight non-parametric models are developed to emulate the behavior described by the power curve of the wind farms. A comparison between the power curve models based on artificial neural networks (ANNs) and those based on fuzzy logic are also proposed. Some of the power curve models based on ANNs and fuzzy inference systems (FISs) are used as well as two new FISs with the proposed new heuristic. An initial pre-training is proposed, resulting from the characteristics derived from the expert inference followed by a transformation of a fuzzy Mamdani system into a fuzzy Sugeno system. Although the presented values by the error indicators are comparable, the results show that the new pre-trained FIS models have better precision compared with the ANN and FIS models. The comparative study is conducted in two wind farms located in northeastern Brazil. The proposed method is a relevant alternative to improve power curve approximation based on an FIS.

【 授权许可】

Unknown