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A review on methods of energy performance improvement towards sustainable manufacturing from perspectives of energy monitoring, evaluation, optimization and benchmarking

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  • Cai, Wei
  • Wang, Lianguo
  • Li, Li
  • Xie, Jun
  • Jia, Shun
  • Zhang, Xugang
  • Jiang, Zhigang
  • Lai, Kee-hung

Abstract

Improving energy performance has been recognized as an effective measure to promote the energy saving and emission reduction and to realize the sustainable development. Methods of improving energy performance towards sustainable manufacturing are numerous and scattered, resulting in insufficiency from the perspective of overall strategies and system integration. After the intensive selection of advanced literatures, about 166 research papers directly related to energy performance improvement are analyzed. A comprehensive review and analysis from multi-perspectives of energy monitoring, evaluation, optimization and benchmarking are performed, which is conducive to understand the energy consumption pattern and take effective energy-saving measures. This paper establishes a framework of energy performance integrated method, and four energy management methods and their energy models in energy monitoring, evaluation, optimization and benchmarking phase are analyzed and summarized. Besides, the proposed framework analyzes potential applications and key advantages, and some challenges and potential opportunities for energy performance improvement methods are discussed. This study will provide a significant foundation for energy-efficient production through various methods application.

Suggested Citation

  • Cai, Wei & Wang, Lianguo & Li, Li & Xie, Jun & Jia, Shun & Zhang, Xugang & Jiang, Zhigang & Lai, Kee-hung, 2022. "A review on methods of energy performance improvement towards sustainable manufacturing from perspectives of energy monitoring, evaluation, optimization and benchmarking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    • Handle: RePEc:eee:rensus:v:159:y:2022:i:c:s1364032122001502
    DOI: 10.1016/j.rser.2022.112227
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    3. Zhang, Jiaqi & Han, Xin & Li, Li & Jia, Shun & Jiang, Zhigang & Duan, Xiangmin & Lai, Kee-hung & Cai, Wei, 2023. "Multi-objective optimisation for energy saving and high efficiency production oriented multidirectional turning based on improved fireworks algorithm considering energy, efficiency and quality," Energy, Elsevier, vol. 284(C).
    4. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2023. "Job scheduling under Time-of-Use energy tariffs for sustainable manufacturing: a survey," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1091-1109.
    5. Ma, Shuaiyin & Ding, Wei & Liu, Yang & Ren, Shan & Yang, Haidong, 2022. "Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries," Applied Energy, Elsevier, vol. 326(C).
    6. Zhu, Minglei & Huang, Haiyan & Ma, Weiwen, 2023. "Transformation of natural resource use: Moving towards sustainability through ICT-based improvements in green total factor energy efficiency," Resources Policy, Elsevier, vol. 80(C).

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