[1]Liao Xiaohui,Zhou Bing,Yang Dongqiang,et al.A Method for Short-term Electricity Price Forecasting Based on HHT[J].Journal of Zhengzhou University (Engineering Science),2016,37(01):10-14.[doi:10.3969/j.issn.1671-6833.201503041]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
37
Number of periods:
2016 01
Page number:
10-14
Column:
Public date:
2016-02-28
- Title:
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A Method for Short-term Electricity Price Forecasting Based on HHT
- Author(s):
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Liao Xiaohui1; Zhou Bing1; Yang Dongqiang1; Wu Jie2
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1. School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan, 450001; 2. Zhengzhou Power Supply Company, Zhengzhou, Henan, 450051
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- Keywords:
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power market; electricity price forecasting; Hilbert-Huang transform; combined forecasting
- CLC:
-
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- DOI:
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10.3969/j.issn.1671-6833.201503041
- Abstract:
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Short-term electricity price forecasting guarantees the maximum benefit of the parties involved in the power market. In view of the fact that the market clearing price has strong randomness and volatility, the paper proposes a combination forecasting model based on Hilbert-Huang transform. The price sequence is decom-posed into a number of intrinsic mode function components and the remainder by using the empirical mode de-composition theory. Different models were built for each intrinsic mode function according to the size of each component’ s average instantaneous frequency. Then the prediction results of each component are added up to obtain the final prediction value. And the model uses the actual data of PJM power market in the United States to test. Compared to the prediction results of any one sole model, this method accuracy were higher than single forecasting model, the maximum absolute error is 1. 53 S|/MWh and the mean absolute percentage error is 1. 61.