期刊论文

Wind speed forecasting based on improved exponential smoothing method and Makov model

中文

电力科学与技术学报

1673-9140

2016

31

1

85-89

10.3969/j.issn.1673-9140.2016.01.013

本校为第一机构

针对传统指数平滑法在风速预测中的不足,搭建基于改进指数平滑法和马尔科夫修正模型的风速组合预测模型。通过梯度优化法快速追踪最优平滑系数α,加快计算效率和提高预测精度;利用马尔科夫模型修正残差,进一步增加预测精度。实验结果表明,该模型在计算效率上,比动态遍历指数平滑法提高近80%;而在预测精度上,比传统指数平滑法和灰色预测法分别提高了27%和32%。该模型对于风速的预测是准确、有效的,具有一定的实用价值。

For the deficiency of traditional exponential smoothing method in forecasting wind speed,this paper proposed an wind speed forecasting method based on the improved exponential smoothing method and Makov correction model.Firstly,optimal smoothing coefficientαwas fastly traced by gradient optimization method to accelerate computational efficiency and improve forecasting accuracy.Then the Markov model was applied to modify residuals and further im-prove the forecasting accuracy.Experimental results show that the proposed model increases the compu...