Abstract
Digital transformation in industry is seen as a key technology enabling decarbonization. It is obvious that measures to increase the energy efficiency and integration of renewable energy technologies must be fostered, and in most cases, these measures need a smart combination of several solution pathways. This results in a significant increase in both the design and operation complexity of these systems. However, there is no clear guidance regarding optimized systems. This work presents a standardized methodology enabling the optimized management of the demand and supply side of an industrial process towards decarbonization. The methodology is presented and showcased based on examples from the food industry and demonstrates how to realize energy efficiency measures and the integration of renewable energy by combining the supply side (SS) and demand side (DS) of industrial processes. The results show that data availability and individualized modeling are major challenges in implementing the methodology. To show the impact of optimization, well-selected key performance indicators (KPIs) are a proper means of evaluation and validation, but it is important to select them on purpose. Therefore, future research should focus on efficient data acquisition, expanding expertise, standardized modeling tools, and KPI definitions.
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