Title

Comparative Analysis of Regression and Neural Network Models for Wind Power

Abstract

This paper compares regression and neural network models for prediction of wind turbine power. The two techniques are first compared theoretically. Then, parameter estimates for the regression model and training of the neural network are completed and the performances of the two models are compared with wind farm data. The regression model is function dependent but the neural network model obtains its prediction through learning. For most cases, the neural network outperforms regression.

Meeting Name

Artificial Neural Networks in Engineering Conference (ANNIE 1998) (1998: Nov. 1-4, St. Louis, MO)

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

791800822

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1998 American Society of Mechanical Engineers (ASME), All rights reserved.

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