Author:
Hermann Julia,Rusche Simon,Moder Linda,Weibelzahl Martin
Abstract
AbstractThe transition from fossil fuels to renewable energy sources poses major challenges for balancing increasingly weather-dependent power supply and demand. Although demand-side energy flexibility, offered particularly by industrial companies, is seen as a promising and necessary approach to address these challenges and realize benefits for companies, its implementation is not yet common practice. Often facing highly complex process landscapes and operational systems, process mining provides significant potential to increase transparency of actual process flows and to discover or reflect existing dependencies and interrelationships of activities, instances or resources. It facilitates the implementation of energy flexibility measures and enables the realization of monetary benefits associated with flexible process operation. This paper contributes to the successful integration of energy flexibility into process operations by presenting a design science research artifact called PM4Flex. This is a prescriptive process monitoring approach that uses linear programming to generate recommendations for pending process flows optimized under fluctuating power prices by utilizing established energy flexibility measures. Thereby, event logs and corresponding company- as well as process-specific constraints are considered. PM4Flex is demonstrated and evaluated based on its implementation as a software prototype, its application to exemplary data from two real-world processes exhibiting power cost savings of up to 75% compared to the original execution, and based on semi-structured expert interviews. PM4Flex provides new design knowledge at the interface of prescriptive process monitoring and the energy domain providing decision support to optimize industrial energy procurement costs.
Funder
Fraunhofer-Institut für Angewandte Informationstechnik FIT
Publisher
Springer Science and Business Media LLC
Reference100 articles.
1. Aggarwal CC (2016) Recommender systems. Springer, Cham
2. Alcázar-Ortega M, Calpe C, Theisen T, Carbonell-Carretero JF (2015) Methodology for the identification, evaluation and prioritization of market handicaps which prevent the implementation of demand response: application to European electricity markets. Energy Policy 86:529–543. https://doi.org/10.1016/j.enpol.2015.08.006
3. Anderson KD, Berges ME, Ocneanu A, Benitez D, Moura JM (2012) Event detection for non intrusive load monitoring. In: 38th Annual Conference on IEEE Industrial Electronics Society, pp 3312–3317
4. Asadinejad A, Tomsovic K (2017) Optimal use of incentive and price based demand response to reduce costs and price volatility. Electr Power Syst Res 144:215–223. https://doi.org/10.1016/j.epsr.2016.12.012
5. Bachmann A, Bank L, Bark C, Bauer D, Dietz B, et al. (2021) Energieflexibel in die Zukunft: Wie Fabriken zum Gelingen der Energiewende beitragen können. VDI_Handlungsempfehlung Oktober 2021. Fraunhofer-Gesellschaft
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Managing Dynamics in and Around Business Processes;Business & Information Systems Engineering;2024-08-30