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

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.

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