This paper focuses on the analysis of prediction of wind speed in the wind farms. The performance of modeling can be analyzed by using the real time data with different heights of the wind mill. Artificial Neural Network is used here to develop models for predicting wind speed in wind farms. The models are mainly based on back propagation neural network and radial basis function neural network. The wind speed prediction is important because it is useful for assisting operational control of wind farms. The effectiveness of these models is demonstrated in this paper. It is found that the root mean square error can be reduced and the uncertainty of prediction and calculation time is also decreased in such a way that the efficiency of prediction is improved.
Key words: Arificial neural networks, prediction, models, back propagation network, radial basis function network, root mean square error.
Copyright © 2023 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0