Wind speed and wind power forecasting models

Author:

Lydia M.1ORCID,Edwin Prem Kumar G.2,Akash R.3

Affiliation:

1. Department of Mechatronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India

2. Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, India

3. Department of Electrical Engineering, IIT Madras, Chennai, India

Abstract

Sustainable energy resources have proved to be the best alternative in the wake of environmental degradation, depletion of ozone layer and ever-increasing demand for energy. Though wind energy is a promising resource, the non-linear nature and non-stationary characteristics of wind have remained a formidable challenge. Variability in wind power has posed numerous challenges in managing the power systems, especially in grid evacuation, penetration and integration. Forecasting wind is one of the powerful solutions to solve this problem. As the penetration of renewable energy sources is poised to increase in future, an accurate prediction can go a long way in helping the electricity grid to perform well. This article presents a review of existing research and recent trends in the forecasting of wind power and speed with a critical analysis of the contribution of every researcher. A review of forecasting technologies, data, time horizons, various forecasting approaches and error metrics has been presented in detail. The plethora of research issues that continue to challenge power system operators, wind farm owners and other stakeholders has been highlighted. The development of models for wind power or wind speed forecasting with excellent reliability and outstanding accuracy is the need of the hour.

Publisher

SAGE Publications

Reference137 articles.

1. Hutchinson M, Zhao F. Global wind energy report 2023, Global Wind Energy Council, Belgium, 2023.

2. Linear and non-linear autoregressive models for short-term wind speed forecasting

3. Wind power forecasting : state-of-the-art 2009.

4. IEC Technical Report 63043 Edition 1.0, 2020-11 Renewable energy power forecasting technology. ISBN 978-2-8322-9079-8, 2022.

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