Linear optimization fusion model based on fuzzy C-means: Case study of energy efficiency evaluation in ethylene product plants

- The linear optimization fusion algorithm based on fuzzy C-means clustering is proposed.
- The energy efficiency benchmark of ethylene plants is obtained by the proposed method.
- The proposed method is valid and efficient in energy efficiency improvement of ethylene plants.

Ethylene production shares the common characteristics of different techniques and scales, high dimension and multi-correlation. However, the existing methods do not take the influence of the technology, scale and materials into account. In order to analyze the energy efficiency of ethylene plants better, this paper proposes a linear optimization fusion model based on fuzzy C-means (FCM) clustering. The FCM clustering is used to obtain the corresponding classification and clustering centers of the large scale time series data of the ethylene production process. Then the mean squares of time-series variables are calculated by various clustering centers. The multidimensional energy efficiency benchmarking of ethylene plants can be extracted by the fusion weighting vectors in linear optimization fusion model. The experimental results indicate that the proposed method intuitively reveals the running state and the operating level of ethylene plants and accurately identify the reason of energy consumption for improving energy efficiency.

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