Conference paper
Computational Efficiency of Economic MPC for Power Systems Operation
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark3
In this work, we propose an Economic Model Predictive Control (MPC) strategy to operate power systems that consist of independent power units. The controller balances the power supply and demand, minimizing production costs. The control problem is formulated as a linear program that is solved by a computationally efficient implementation of the Dantzig-Wolfe decomposition.
To make the controller suitable for realtime applications, we investigate a suboptimal MPC scheme, introducing an early termination strategy to the Dantzig-Wolfe algorithm. Simulations demonstrate that the early termination technique substantially reduces the computation time.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2013 |
| Pages: | 1-5 |
| Proceedings: | 2013 4th IEEE PES Innovative Smart Grid Technologies Europe |
| ISBN: | 1479929840 , 1479929859 , 9781479929849 and 9781479929856 |
| Types: | Conference paper |
| DOI: | 10.1109/ISGTEurope.2013.6695361 |
| ORCIDs: | Poulsen, Niels Kjølstad and Jørgensen, John Bagterp |
Dantzig-Wolfe algorithm Dantzig-Wolfe decomposition Economics Generators Linear programming Power systems Predictive control Production Real-time systems computational efficiency control problem controller controllers early termination technique economic MPC economic model predictive control independent power units linear program linear programming power supply and demand power system control power system economics power systems power systems operation predictive control production costs suboptimal MPC scheme
