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Leveraging Dynamic Pricing and Real-Time Grid Analysis: A Danish Perspective on Flexible Industry Optimization

Sreelatha Aihloor Subramanyam, Sina Ghaemi, Hessam Golmohamadi, Amjad Anvari-Moghaddam and Birgitte Bak-Jensen ()
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Sreelatha Aihloor Subramanyam: Department of Energy, Aalborg University, 9220 Aalborg, Denmark
Sina Ghaemi: Department of Energy, Aalborg University, 9220 Aalborg, Denmark
Hessam Golmohamadi: Department of Energy, Aalborg University, 9220 Aalborg, Denmark
Amjad Anvari-Moghaddam: Department of Energy, Aalborg University, 9220 Aalborg, Denmark
Birgitte Bak-Jensen: Department of Energy, Aalborg University, 9220 Aalborg, Denmark

Energies, 2025, vol. 18, issue 15, 1-18

Abstract: Flexibility is advocated as an effective solution to address the growing need to alleviate grid congestion, necessitating efficient energy management strategies for industrial operations. This paper presents a mixed-integer linear programming (MILP)-based optimization framework for a flexible asset in an industrial setting, aiming to minimize operational costs and enhance energy efficiency. The method integrates dynamic pricing and real-time grid analysis, alongside a state estimation model using Extended Kalman Filtering (EKF) that improves the accuracy of system state predictions. Model Predictive Control (MPC) is employed for real-time adjustments. A real-world case studies from aquaculture industries and industrial power grids in Denmark demonstrates the approach. By leveraging dynamic pricing and grid signals, the system enables adaptive pump scheduling, achieving a 27% reduction in energy costs while maintaining voltage stability within 0.95–1.05 p.u. and ensuring operational safety. These results confirm the effectiveness of grid-aware, flexible control in reducing costs and enhancing stability, supporting the transition toward smarter, sustainable industrial energy systems.

Keywords: dynamic pricing; MILP; real-time grid analysis; Kalman filter; industrial energy optimization; flexible assets; aquaculture case study; Model Predictive Control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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