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http://localhost:8080/xmlui/handle/123456789/3740Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Santhosh, Madasthu | - |
| dc.contributor.author | Venkaiah, Chintham | - |
| dc.contributor.author | Vinod Kumar, D.M. | - |
| dc.date.accessioned | 2025-12-26T10:14:39Z | - |
| dc.date.available | 2025-12-26T10:14:39Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.citation | 10.1002/eng2.12178 | en_US |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/3740 | - |
| dc.description | NITW | en_US |
| dc.description.abstract | Wind power is playing a pivotal part in global energy growth as it is clean and pollution-free. To maximize profits, economic scheduling, dispatching, and planning the unit commitment, there is a great demand for wind forecasting techniques. This drives the researchers and electric utility planners in the direc tion of more advanced approaches to forecast over broader time horizons. Key prediction techniques use physical, statistical approaches, artificial intelligence techniques, and hybrid methods. An extensive review of the current forecast ing techniques, as well as their performance evaluation, is here presented. The techniques used for improving the prediction accuracy, methods to overcome major forecasting problems, evolving trends, and further advanced applications in future research are explored | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Engineering Reports | en_US |
| dc.subject | Artificial intelligence | en_US |
| dc.subject | Electric utilities | en_US |
| dc.title | Current advances and approaches in wind speed and wind power forecasting for improved renewable energy integration: A review | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Electrical Engineering | |
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