Short-Term Power Load Forecasting Based on EMD-Grey Model
American Journal of Electrical Power and Energy Systems
Volume 7, Issue 4, July 2018, Pages: 42-49
Received: Jul. 30, 2018;
Accepted: Aug. 14, 2018;
Published: Sep. 4, 2018
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Dong Jun, School of Economics and Management, North China Electric Power University, Beijing, China
Wang Pei, School of Economics and Management, North China Electric Power University, Beijing, China
Dou Xihao, School of Economics and Management, North China Electric Power University, Beijing, China
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With the issuance of "electricity reform No. 9 document" in 2015, a new round of power system reform in China has been continuously pushed forward. With the gradual development of the pilot spot market in various provinces, the importance of load forecasting to the various main bodies of the spot power market has been constantly revealed. In order to improve the accuracy of short-term load forecasting in the spot market, and better highlight the randomness, periodicity and related trend of load fluctuation, this paper proposes a short-term load forecasting based on grey model and the EMD combination model, predict the future 24-hour load. In other words, GM(1,1) is used to predict the residual value sequence of EMD decomposition. In order to ensure the stability of the residual value sequence, improve the accuracy of the prediction and improve the effect of short-term load forecasting. Combined with MATLAB tools, the combined prediction model was simulated and verified by using the America PJM power market load data. The comparison results of the combined model with the single GM(1,1) and GM(1,2) respectively show that the combined model can significantly improve the accuracy of load forecasting compared with the traditional grey model method, providing the method guidance for load forecasting to better participate in the demand response under the new market environment.
Load Forecasting, EMD, Grey Model, Combination Model
To cite this article
Short-Term Power Load Forecasting Based on EMD-Grey Model, American Journal of Electrical Power and Energy Systems.
Vol. 7, No. 4,
2018, pp. 42-49.
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
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