Synthetic load profile generation for production chains in energy intensive industrial subsectors via a bottom-up approach

Paul Josef Binderbauer, Thomas Kienberger, Thomas Staubmann

Publikation: Beitrag in FachzeitschriftArtikelForschungBegutachtung

1 Zitat (Scopus)


Iron & Steel, Pulp & Paper, Non-Metallic Minerals and Chemical & Petrochemical are the most energy intensive subsectors, even though they utilise only a limited range of production processes compared to other sectors like Machinery or Food & Beverages. To support future efforts for decarbonising the European industry, this study aims to develop a methodology to correctly and dynamically depict all relevant production processes of the mentioned subsectors and to generate synthetic load profiles (LP)1 based upon their consumption and generation behaviour. In a first step, the energy intensive subsectors and their main production processes are identified. A standardised research approach is used to correctly depict their characteristics e.g. runtime, energy consumption and generation, unit sizes etc. Next, a methodology for modelling the timely behaviour of these production processes and for generating synthetic LPs is developed. This method is based upon the bottom-up approach of discrete-event simulation combined with stochastics. The developed methodology is then implemented into the simulation software Ganymed. Finally, the results of this methodology are validated via a case study, modelling the primary steel production route of an Austrian steel mill. In overall, the synthetic electricity LP shows good approximations to the measured one with a mean absolute percentage error of 6.08% for the simulated five days in total. However, a stronger deviation of the generated LP compared to the measured counterpart can be noted at the last two days. This deviation results from a reduction of the capacity during the real life production. This, however, can be taken into account in the synthetic generation given a more extensive data basis. Consequently, Ganymed can be deemed as a suitable software for generating energy consumption and generation behaviour of processes and production chains of energy intensive industries.
FachzeitschriftJournal of Cleaner Production
Ausgabenummer10 January
Frühes Online-Datum7 Dez. 2021
PublikationsstatusVeröffentlicht - 10 Jan. 2022

Bibliographische Notiz

Funding Information:
This work was carried out as part of the NEFI_Lab project. The NEFI_Lab project is supported with the funds from the Climate and Energy Fund and implemented in the framework of the RTI-initiative “Flagship region Energy”.

Publisher Copyright:
© 2021

Dieses zitieren