Abstract
Energy management and optimization play a key effect in the sustainable development. However, the uncertain data has a direct impact on the production prediction and energy optimization of complex petrochemical industries. Therefore, this paper proposes a novel energy management and optimization model based on the fuzzy extreme learning machine (FELM) method integrated the fuzzy set theory. The minimal, the median and the maximal values of the energy consumption data are obtained by data fuzzification to solve the problem of the fluctuation and uncertainty data. And the cross recombination of triangular fuzzy numbers (TFNs) is applied in the training of the FELM. Moreover, the upper and the lower limits of efficiency values are obtained on the basis of the network generalization to analyze the energy conservation and saving potentials. Furthermore, the FELM has better predictive performance and training speed than fuzzy error back propagation network (FBP) and fuzzy radical basis function network (FRBF) though University of California Irvine (UCI) standard datasets. Finally, the proposed method is applied to manage and optimize the energy status of China ethylene industry in complex petrochemical industries. The experimental results show that the proposed method is effective and applicable in the energy-saving potential, which is indicated up to about 15%.
Published Version
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