TY - GEN

T1 - A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio

A1 - Standardi,Laura

A1 - Edlund,Kristian

A1 - Poulsen,Niels Kjølstad

A1 - Jørgensen,John Bagterp

AU - Standardi,Laura

AU - Edlund,Kristian

AU - Poulsen,Niels Kjølstad

AU - Jørgensen,John Bagterp

PB - Technical University of Denmark

PY - 2012

Y1 - 2012

N2 - Future power systems will consist of a large number of decentralized power producers and a large number of controllable power consumers in addition to stochastic power producers such as wind turbines and solar power plants. Control of such large scale systems requires new control algorithms. In this paper, we formulate the control of such a system as an Economic Model Predictive Control (MPC) problem. When the power producers and controllable power consumers have linear dynamics, the Economic MPC may be expressed as a linear program and we apply Dantzig-Wolfe decomposition for solution of this linear program. The Dantzig-Wolfe decomposition algorithm for Economic MPC is tested on a simulated case study with a large number of power producers. The Dantzig-Wolfe algorithm is compared to a standard linear programming (LP) solver for the Economic MPC. Simulation results reveal that the Dantzig-Wolfe algorithm is faster than the standard LP solver and enables solution of larger problems.

AB - Future power systems will consist of a large number of decentralized power producers and a large number of controllable power consumers in addition to stochastic power producers such as wind turbines and solar power plants. Control of such large scale systems requires new control algorithms. In this paper, we formulate the control of such a system as an Economic Model Predictive Control (MPC) problem. When the power producers and controllable power consumers have linear dynamics, the Economic MPC may be expressed as a linear program and we apply Dantzig-Wolfe decomposition for solution of this linear program. The Dantzig-Wolfe decomposition algorithm for Economic MPC is tested on a simulated case study with a large number of power producers. The Dantzig-Wolfe algorithm is compared to a standard linear programming (LP) solver for the Economic MPC. Simulation results reveal that the Dantzig-Wolfe algorithm is faster than the standard LP solver and enables solution of larger problems.

KW - Economic Model Predictive Control

KW - Linear programming

KW - Distributed Optimization

KW - Power systems

BT - The 10th European Workshop on Advanced Control and Diagnosis (ACD 2012)

T2 - The 10th European Workshop on Advanced Control and Diagnosis (ACD 2012)

ER -