| Issue |
E3S Web Conf.
Volume 472, 2024
International Conference on Renewable Energy, Green Computing and Sustainable Development (ICREGCSD 2023)
|
|
|---|---|---|
| Article Number | 03008 | |
| Number of page(s) | 13 | |
| Section | Sustainable Development | |
| DOI | https://doi.org/10.1051/e3sconf/202447203008 | |
| Published online | 05 January 2024 | |
Wind Power Prediction Model Using Artificial Neural Network
1 Dept. of Electrical and Electronics Engineering, Editorial Department, Goa College of Engineering, Ponda, India
2 Dept. of Electrical and Electronics Engineering, Editorial Department, Goa College of Engineering, Ponda, India
* email: fedoradias@gmail.com
Renewable energy plays a vital role in energy management and hence resultant sus-tainable development. The uncertainty of its availability is the point of concern. Hence the optimal usage and prediction of its availability become very critical. Several methods of wind energy forecasting at any given location are available in the literature. In this article, a machine learning-based wind energy forecasting method is suggested. The wind data and related parameters at Satara district of Maharashtra state in India are obtained. ANN (Artificial Neural Network) model is developed, trained, tested, and validated for the available data. The results obtained for future wind energy predicted approximately match the actual values.
Key words: Artificial Neural Network / Machine Learning
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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