Data and optimization model of an industrial heat transfer station to increase energy flexibility

Abstract

Abstract Nations and companies are forced to reduce CO2 emissions and decelerate global warming. In this development, the transition of the heating sector is still in its infancy despite the relatively large share of thermal energy in the total energy consumption. Industrial companies can contribute significantly to reduce CO2 emissions by using waste heat through connecting their industrial energy supply system (IESS) to a district heating system (DHS). This paper focuses on emission reduction potential of an (industrial) heat transfer station (HTS) regarding energy flexibility and sector coupling required for the successful integration of industrial waste heat. To optimize the operating behaviour of the HTS, a data and optimization model is integrated into a digital twin (DT) based on reference architecture model for industry 4.0 (RAMI4.0). Within the DT, the information, functional and business layer are modeled. The effects of operating the HTS supported by central modules of the DT are evaluated on one year’s data of an IESS of a real industrial site. The results show a potential operating cost reduction by 6 % for the IESS and increases in profits of 1.3 % for the DHS. Scope 2 emissions can be reduced by 25 % for the IESS and 180 % for the DHS respectively, strongly depending on emission factors and allocation methods.

Keywords

• Industrial energy supply systems
• District heating systems
• Smart grids
• Heat transfer station
• Digital twin
• Optimization