Physics-Based Modeling and Parameter Tracing for Industrial Demand-Side Management Applications: A Novel Approach

Dominik Leherbauer () and Peter Hehenberger
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Dominik Leherbauer: “Smart Mechatronics Engineering” Research Group, University of Applied Sciences Upper Austria, 4600 Wels, Austria
Peter Hehenberger: “Smart Mechatronics Engineering” Research Group, University of Applied Sciences Upper Austria, 4600 Wels, Austria

Sustainability, 2024, vol. 16, issue 5, 1-35

Abstract: The transition to sustainable energy sources presents significant challenges for energy distribution and consumption systems. Specifically, the intermittent availability of renewable energy sources and the decreasing usage of fossil fuels pose challenges to energy flexibility and efficiency. An approach to tackle these challenges is demand-side management, aiming to adapt energy consumption and demand. A key requirement for demand-side management is the traceability of the energy flow among individual energy consumers. In recent years, advancements in industrial information and communication technology have provided additional potential for data acquisition. Complementary to acquired data, a physics-based modeling and analysis approach is proposed, which describes the energy consumption with physical parameters. This results in comprehensive options for monitoring actual energy consumption and planning future energy demand supporting energy efficiency and demand-response goals. To validate the proposed approach, a case study with a 3D printer covering approximately 110 h of active printing time is conducted. The medium-term study results indicate a consistent parameter trend over time, suggesting its conceptual suitability for industrial application. The approach helps to monitor energy efficiency among manufacturing assets by identifying peak loads and consumption hotspots, and provides parameters to estimate energy consumption of manufacturing processes. Results indicate up to 50% energy savings when switching the printing material and indicate further potentials.

Keywords: demand-side management; model-predictive control; model-based engineering; demand-response; load management; parameter estimation; energy efficiency; industrial energy management; energy simulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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