Super-resolution perception for wind power forecasting by enhancing historical data

As an important part of renewable energy, wind power is crucial to the realization carbon neutrality. It worth studying on how accurately predict output so that it can be integrated into grid as much possible enhance its utilization rate. In this article, a data enhancement method and framework are proposed assist forecasting. The uses super-resolution perception technology first detect completeness correctness historical meteorological collected by industrial devices. Then, detected errors corrected missing recovered make complete. frequency then increased using become complete high-frequency data. Based enhanced with more detailed characteristics, accurate forecasts achieved, thereby improving rate power. Experiments based public datasets used demonstrate effectiveness framework. With framework, higher information providing support for prediction was not before.