Title: Energy conservation and recycling transformation of clean energy heating based on artificial intelligence

Authors: Shuang Ma; Qi Zhao; Hao Wang; Xin Song

Addresses: School of Energy and Power, Changchun Institute of Technology, Changchun 130012, Jilin, China; Construction Energy Supply and Indoor Environment Control Engineering Research Center of Jilin Province, Changchun 130012, Jilin, China ' School of Energy and Power, Changchun Institute of Technology, Changchun 130012, Jilin, China; Construction Energy Supply and Indoor Environment Control Engineering Research Center of Jilin Province, Changchun 130012, Jilin, China ' School of Energy and Power, Changchun Institute of Technology, Changchun 130012, Jilin, China; Construction Energy Supply and Indoor Environment Control Engineering Research Center of Jilin Province, Changchun 130012, Jilin, China ' School of Data Science and Engineering, South China Normal University, Shanwei 516600, Guangdong, China

Abstract: There are many problems in the process of heating energy saving, such as low energy utilisation efficiency, poor energy circulation effect and failure of non-renewable energy to clean energy transformation. In this paper, the application of artificial intelligence (AI) to clean energy heating, energy saving and recycling transformation is proposed, and relevant comparative experiments and questionnaires are designed. The comparative experiment results show that in the traditional clean energy heating energy-saving equipment, the energy recycling rate is basically controlled in the range of 60%-70%, but there are four times the energy recycling rate exceeds the standard; in clean energy heating and energy-saving devices using artificial intelligence, the energy recovery rate of clean energy is basically controlled between 85% and 95%, and no energy recovery rate exceeds this range. This study shows that artificial intelligence has a better effect on energy recycling of clean energy heating and energy-saving.

Keywords: clean energy; energy conservation of heat supply; recycling and transformation; artificial intelligence.

DOI: 10.1504/IJMPT.2023.136538

International Journal of Materials and Product Technology, 2023 Vol.67 No.3/4, pp.362 - 377

Received: 21 Mar 2023
Accepted: 22 Sep 2023
Published online: 05 Feb 2024 *

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