Wind speed conformal prediction in wind farm based on algorithmic randomness theory

An approach of a mean hourly wind speed conformal prediction in wind farm is proposed. Conformal prediction is a new prediction methodology. It can be used not just to make predictions but also to estimate the confidence under the usual independent and identically distributed assumption. Based on support vector regression, wind speed regions are predicted by inductive confidence machine. Wind speed region's width and confidence reflect the accuracy and reliability of the prediction. Compared to bare wind speed forecasting, the accuracy and reliability of the prediction can be used to reduce the risk of decision-making. Experimental results are given by using wind mean hourly speed measured in wind farm, and the application of the method carried out a detailed analysis and verification.