Energy End-Use Categorization and Performance Indicators for Energy Management in the Engineering Industry

Abstract

Energy efficiency (EE) improvement is one of the most crucial elements in the decarbonization of industry. EE potential within industries largely remains untapped due to the lack of information regarding potential EE measures (EEM), knowledge regarding energy use, and due to the existence of some inconsistencies in the evaluation of energy use. Classification of energy end-using processes would increase the understanding of energy use, which in turn would increase the detection and deployment of EEMs. The study presents a novel taxonomy with hierarchical levels for energy end-use in manufacturing operations for the engineering industry, analyzes processes in terms of energy end-use (EEU) and CO2 emissions, and scrutinizes energy performance indicators (EnPIs), as well as proposing potential new EnPIs that are suitable for the engineering industry. Even though the study has been conducted with a focus on the Swedish engineering industry, the study may be generalizable to the engineering industry beyond Sweden.

Barriers to and Drivers of Energy Management in Swedish SMEs

“…The absence of proper energy measurement prevents the organizations from knowing where energy is lost and where potential efficiency measures are found. Energy mapping is important since it allows for knowledge about energy end-use for processes in different levels within companies [85]. SMEs are not obligated to undertake energy audits every fourth year and, thus, do not normally have any energy mapping of their own processes such as for large companies.…”

Goals and measures for analyzing power consumption data in manufacturing enterprises

“…Proposed implementations are therefore often using stream processing techniques and tools (see also the following Section 2.3). Several studies point out that many types of power consumption analysis require consumption data at different levels (Vikhorev et al 2013;Shrouf and Miragliotta 2015;Kanchiralla et al 2020). Whereas, for example, the effect of overall power consumption optimizations can be evaluated with data of the overall power consumption, detecting defects in machines requires to acquire data at machine-level.…”

Optimization of Energy-Efficient Functioning of the Oil and Gas Sector of the Economy Through Digitalization and Resource Conservation

“…The dynamically developing world economy is accompanied by qualitative changes, which requires from science and practice new approaches to the management of technological processes, industrial enterprises, and complexes. The works of foreign researchers are devoted to the issues of energy efficiency, reflecting the investment aspect of rationalizing energy consumption (Ayres et al, 2013), modeling the dependence of energy efficiency on external factors, impact assessment based on the Efficient reliability index (Barzegar et al, 2020), "Rebound effect" in ensuring energy efficient industrial production (Bongers, 2020), social aspect of energy saving development (Dunlop, 2019), solutions to optimize production to minimize energy costs (Gong et al, 2015), directions for improving energy efficiency and decarbonization of the machinebuilding industry (Kanchiralla et al, 2020), a systematic approach to energy efficiency and organizational culture of the enterprise (Koenig, 2020), energy management of buildings and structures (Marinakis, 2020). The works of Russian scientists have also made a significant contribution to solving the issues of increasing the energy efficiency of industrial enterprises.…”