Journal article
A Dantzig-Wolfe decomposition algorithm for linear economic model predictive control of dynamically decoupled subsystems
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Ørsted A/S3
Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
Center for Energy Resources Engineering, Centers, Technical University of Denmark5
CITIES - Centre for IT-Intelligent Energy Systems, Centers, Technical University of Denmark6
This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input limits, input rate limits, and soft output limits.
The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm is significantly faster than both state-of-the-art linear programming solvers, and a structure exploiting implementation of the alternating direction method of multipliers.
It is also demonstrated that the control strategy presented in this paper can be tuned using a weighted ℓ1-regularization term. In the presence of process and measurement noise, such a regularization term is critical for achieving a well-behaved closed-loop performance.
Language: | English |
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Year: | 2014 |
Pages: | 1225-1236 |
ISSN: | 18732771 and 09591524 |
Types: | Journal article |
DOI: | 10.1016/j.jprocont.2014.05.013 |
ORCIDs: | Poulsen, Niels Kjølstad , Madsen, Henrik and Jørgensen, John Bagterp |