Algorithmic Maximization of Energy Productivity to Increase Energy Savings in Production Processes

Abstract

The industrial sector accounts for 25 % of Germany's gross domestic product and 28 % of total final energy consumption in 2022. This sector is therefore both environmentally and economically significant. With renewables accounting for only 6.3 % of final energy production in this sector in 2022, the environmental need for transformation in industrial energy infrastructure is high. To remain globally competitive, the energy productivity of affected production processes must be maintained. This results in highly complex design and operation problems that require algorithmic support. Therefore, this article presents a mathematical programming approach to maximize energy productivity for surface hardening. The multi-objective optimization integrates process models with an evolutionary algorithm in a unified modeling and solution approach. The optimization provides viable solutions to derive adaption of process parameters capable of reducing the energy intensity of the related production process. The approach is validated by its application to the gas heated chamber oven of the ETA Research Factory