WIND SPEED CONFORMAL PREDICTION IN WIND FARM BASED ON ALGORITHMIC RANDOMNESS THEORY

摘要：

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 regions 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.

关键词： Wind speed prediction Inductive confidence machine Support vector regression Predictive region

作者: GUO-RUI JI ZE DONG DONG-FENG WANG PU HAN DA-PING XU

作者单位: School of Energy and Power Engineering, North China Electric Power University, Beijing 102206, China School of Control Science and Engineering, North China Electric Power University, Baoding 071003, Ch

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 131-135

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）