WSEAS Transactions on Systems and Control
Print ISSN: 1991-8763, E-ISSN: 2224-2856
Volume 11, 2016
Power System Middle-Term Load Forecasting Based on CEEMD with Fuzzy Entropy and Elman ANN
Authors: , , ,
Abstract: In this paper, a new combination prediction approach was proposed and applied to improve the middle-term electric load forecasting precision. Firstly, the load sequences were decomposed into a limited number of load sub-temporal sequences with different characteristics, which avoids the large computing scale problems of local analysis of load series. Then, the Elman prediction models were constructed by the feature analysis for each sub-temporal sequence respectively. And the final prediction valves were given by the superposition of each sub sequences prediction. The approach is applied to EUNITE’s middle term load forecasting. A comparison of our approach to existing prediction methods is also given. Simulation results show that the new model proposed in this paper can significantly improve the load prediction accuracy.
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Keywords: middle-term load forecasting, Complementary Ensemble Empirical Mode Decomposition (CEEMD), Fuzzy Entropy, Elman Neural Network
Pages: 112-118
WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 11, 2016, Art. #15