Title: Evaluation method for energy saving and emission reduction effects of high energy-consuming enterprises based on K-means clustering

Authors: Liyu Huang; Miaozhuang Cai; Yin Zheng; Yuanliang Zhang

Addresses: Measurement Center of Guangzhou Power Supply Bureau of Guangdong Power Grid, Guangzhou, 511495, China ' Measurement Center of Guangzhou Power Supply Bureau of Guangdong Power Grid, Guangzhou, 511495, China ' Measurement Center of Guangzhou Power Supply Bureau of Guangdong Power Grid, Guangzhou, 511495, China ' Measurement Center of Guangzhou Power Supply Bureau of Guangdong Power Grid, Guangzhou, 511495, China

Abstract: In order to quantitatively analyse the effect of energy conservation and emission reduction control of high energy consuming enterprises, an evaluation model of energy conservation and emission reduction effect of high energy consuming enterprises based on K-means clustering was proposed. In this study, the target object of energy saving and emission reduction effect evaluation is selected first, and the optimisation state model of energy saving and emission reduction effect evaluation is constructed. Then, dynamic feature extraction is carried out on model parameters, and the K-means data clustering algorithm is adopted to conduct block fusion clustering processing on characteristic values. Finally, expert knowledge base and empirical model library are constructed to realise energy saving and emission reduction control of high-energy-consuming enterprises. The test results show that this method can reduce the energy cost, develop a scientific management plan and ensure the realisation of energy conservation and emission reduction targets.

Keywords: K-means clustering; high energy-consuming enterprises; energy saving; emission reduction; effect evaluation; profitability indicators.

DOI: 10.1504/IJETP.2023.134164

International Journal of Energy Technology and Policy, 2023 Vol.18 No.3/4/5, pp.298 - 311

Received: 26 Apr 2023
Accepted: 03 Jul 2023
Published online: 12 Oct 2023 *

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