A New Multi-Resolution Closed-Loop Wind Power Forecasting Method

By the increasing number and size of wind farms, wind generation forecasting has become a basic requirement for their connection to the power grid; otherwise, power system operators and electricity market participants cannot make the right decisions and may incur significant costs and penalties. In this paper, a new multi-resolution closed-loop wind power forecasting method with a difference signal feedback loop is proposed. Within the proposed method, wind power is initially predicted in two different resolutions (such as with hourly and sub-hourly time steps) by two low/high-resolution pre-predictors and then the inconsistency between their predictions is measured through the difference signal. The generated difference signal is used as a guide for the two low/high-resolution wind power post-predictors. If their wind power forecasts are inconsistent, the difference signal is updated and used as the feedback for the low/high-resolution post-predictors. This closed-loop forecasting-updating process is iterated until the post-predictors reach consistent results. To evaluate the performance of the proposed multi-resolution closed-loop method, it is tested on two different real-world wind farms and the results are compared with the results of several other widely used/recently published wind power forecast methods using various error metrics and different forecast horizons.

Automated summary

This paper proposes a new multi-resolution closed-loop wind power forecasting method that improves the accuracy of wind power prediction by making predictions at two different resolutions and measuring inconsistencies through a difference signal.