首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model
Institution:1. Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA;2. Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, MI, USA;3. Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, MI, USA
Abstract:Electricity consumption forecasting has been always playing a vital role in power system management and planning. Inaccurate prediction may cause wastes of scarce energy resource or electricity shortages. However, forecasting electricity consumption has proven to be a challenging task due to various unstable factors. Especially, China is undergoing a period of economic transition, which highlights this difficulty. This paper proposes a time-varying-weight combining method, i.e. High-order Markov chain based Time-varying Weighted Average (HM-TWA) method to predict the monthly electricity consumption in China. HM-TWA first calculates the in-sample time-varying combining weights by quadratic programming for the individual forecasts. Then it predicts the out-of-sample time-varying adaptive weights through extrapolating these in-sample weights using a high-order Markov chain model. Finally, the combined forecasts can be obtained. In addition, to ensure that the sample data have the same properties as the required forecasts, a reasonable multi-step-ahead forecasting scheme is designed for HM-TWA. The out-of-sample forecasting performance evaluation shows that HM-TWA outperforms the component models and traditional combining methods, and its effectiveness is further verified by comparing it with some other existing models.
Keywords:Monthly electricity consumption in China  Time-varying-weight combining method  High-order Markov chain model  Multi-step-ahead combination forecasting  Out-of-sample forecasting accuracy
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号