A robust combination approach for short-term wind speed forecasting and analysis

报告题目：A robust combination approach for short-term wind speed forecasting and analysis

报告人：胡建明    广州大学

报告时间：2017年6月29日（星期四）下午14：00-15：00

报告地点：研教楼307

校内联系人：宋慧    联系电话：84708351-8123

Abstract: With the increasing importance of wind power as a component of power systems, the problems induced by the stochastic and intermittent nature of wind speed have compelled system operators and researchers to search for more reliable techniques to forecast wind speed. This paper proposes a combination model for probabilistic short-term wind speed forecasting. In this proposed hybrid approach, EWT is employed to extract meaningful information from a wind speed series by designing an appropriate wavelet filter bank. The GPR model is utilized to combine independent forecasts generated by various forecasting engines (ARIMA, ELM, SVM and LSSVM) in a nonlinear way rather than the commonly used linear way. The proposed approach provides more probabilistic information for wind speed predictions besides improving the forecasting accuracy for single-value predictions. The effectiveness of the proposed approach is demonstrated with wind speed data from two wind farms in China. The results indicate that the individual forecasting engines do not consistently forecast short-term wind speed for the two sites, and the proposed combination method can generate a more reliable and accurate forecast.

报告人介绍：

胡建明，广州大学聘任副教授，于2016年12月毕业于兰州大学数学与统计学院，2015年8月---2016年8月期间，赴加拿大女王大学进行联合培养，从事通过多重生物标签进行癌症治疗益处的预测研究。目前以第一作者或通讯作者发表SCI论文7篇（一区4篇，二区3篇），总SCI被引用次数超过102次，其中1篇被ESI指标列为领域学科的高引用论文，并担任多个SCI国际期刊的审稿人。

研究兴趣

应用统计理论与方法，时间序列，统计学习，