Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8114374 | Renewable and Sustainable Energy Reviews | 2016 | 7 Pages |
Abstract
The selection of training data for establishing a model directly affects the prediction precision. Wind power has the characteristic of daily similarity. The corresponding meteorological data also has the characteristic of daily similarity. This paper proposes a new model with cluster analysis of the numerical weather prediction information. The similar day with the predicted day is searched as training sample to a generalized regression neural network model. The numerical weather prediction data and actual wind power data from a wind farm are used in this study to test the model. The prediction results show that correct cluster analysis method is a useful tool in day-ahead wind power prediction.
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Lei Dong, Lijie Wang, Shahnawaz Farhan Khahro, Shuang Gao, Xiaozhong Liao,