Computational Efficiency of Economic MPC for Power Systems Operation

Laura Standardi; Niels Kjølstad Poulsen; John Bagterp Jørgensen; Leo Emil Sokoler

doi:10.1109/ISGTEurope.2013.6695361

Computational Efficiency of Economic MPC for Power Systems Operation

Laura Standardi, Niels Kjølstad Poulsen, John Bagterp Jørgensen, Leo Emil Sokoler

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

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.

Original language	English
Title of host publication	Proceedings of the 2013 4th IEEE PES Innovative Smart Grid Technologies Europe
Number of pages	5
Publisher	IEEE
Publication date	2013
DOIs	https://doi.org/10.1109/ISGTEurope.2013.6695361
Publication status	Published - 2013
Event	2013 4th IEEE PES Innovative Smart Grid Technologies Europe - Technical University of Denmark (DTU), Lyngby, Denmark Duration: 6 Oct 2013 → 9 Oct 2013 Conference number: 4 http://www.ieee-isgt-2013.eu/

Conference

Conference	2013 4th IEEE PES Innovative Smart Grid Technologies Europe
Number	4
Location	Technical University of Denmark (DTU)
Country/Territory	Denmark
City	Lyngby
Period	06/10/2013 → 09/10/2013
Internet address	http://www.ieee-isgt-2013.eu/

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title = "Computational Efficiency of Economic MPC for Power Systems Operation",

abstract = "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.",

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AB - 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.

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ER -

Computational Efficiency of Economic MPC for Power Systems Operation

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