Review of Recent Advances in Long-Term Wind Speed and Power Forecasting
- Yihai Zhang
, - Yusuke Hiraga
Abstract
This review examines the advancements and methodologies in long-term
wind speed and power forecasting. It emphasizes the importance of these
techniques in the integration of wind energy into power systems. The
study covers a range of forecasting time horizons from monthly to
multiyear forecasts. It highlights the diversity of applications and
methodologies necessary to address the inherent variability and
unpredictability of wind energy. Various forecasting methods including
statistical models, machine learning techniques, and hybrid models are
discussed in detail. The discussions demonstrate their effectiveness in
improving the forecast accuracy and reliability across different
temporal and geographical scales. The review identifies significant
challenges such as model complexity, data limitations, and the need for
forecasts to accommodate regional variabilities. The future directions
include enhancing model integration, using higher-resolution data, and
increasing collaborative efforts across fields to refine the forecasting
methodologies. This comprehensive analysis aims to advance the knowledge
on wind forecasting, facilitate the efficient integration of wind power
into global energy systems, and contribute to sustainable energy
development goals.Submission Checks Completed
Assigned to Editor
Reviewer(s) Assigned
01 Jul 2024Review(s) Completed, Editorial Evaluation Pending
13 Jul 2024Reviewer(s) Assigned