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The identification and classification of energy waste for efficient energy supervision in manufacturing factories

D. Geng, S. Evans and Y. Kishita

Renewable and Sustainable Energy Reviews, 2023, vol. 182, issue C

Abstract: To respond to global climate change, “Net-Zero” targets have been set up by different governments, organizations, companies, etc. In this regard, manufacturing companies are urged to improve energy efficiency of their production systems. Reducing unnecessary energy consumption, namely energy waste, is therefore becoming critical. Unfortunately, the concept of energy waste has not been clearly defined and classified in both academia and industry. This study aims to uncover the key characteristics of energy waste through an interview-based case study. In total, twenty-five practitioners in different manufacturing factories from China, the UK, Japan, Germany, Austria, and Kenya were interviewed. These interviewees believe that on average energy performance can be improved by 10–20% through energy waste management. Besides, less energy waste results in more stable energy consumption, which can facilitate firms to conduct energy supervision more easily and accurately. Based on the analysis of these cases, an energy waste analytic framework was developed. Thirteen types of energy waste were identified and classified into four categories: 1) management-related behavioural energy waste (Mb-EW); 2) management-related technical energy waste (Mt-EW); 3) technology-related energy waste (T-EW); and 4) design-related energy waste (D-EW). A “step-by-step” strategy is then proposed for reducing energy waste. Both research and development (R&D) efforts and capacity-building efforts should be made to further reduce energy waste. Finally, future research directions are raised, including tools development for reducing energy waste and preparing assessment indicators on energy waste.

Keywords: Energy waste; Case study; Identification; Classification; Energy efficiency (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.rser.2023.113409

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