### Abstract

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.

Original language | English |
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Title of host publication | The 10th European Workshop on Advanced Control and Diagnosis (ACD 2012) |

Number of pages | 8 |

Publisher | Technical University of Denmark |

Publication date | 2012 |

Publication status | Published - 2012 |

Event | 10th European Workshop on Advanced Control and Diagnosis - Technical University of Denmark, Kgs. Lyngby, Denmark Duration: 8 Nov 2012 → 9 Nov 2012 http://indico.conferences.dtu.dk/conferenceDisplay.py?confId=108 |

### Conference

Conference | 10th European Workshop on Advanced Control and Diagnosis |
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Location | Technical University of Denmark |

Country | Denmark |

City | Kgs. Lyngby |

Period | 08/11/2012 → 09/11/2012 |

Internet address |

### Keywords

- Economic Model Predictive Control
- Linear programming
- Distributed Optimization
- Power systems

## Cite this

Standardi, L., Edlund, K., Poulsen, N. K., & Jørgensen, J. B. (2012). A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio. In

*The 10th European Workshop on Advanced Control and Diagnosis (ACD 2012)*Technical University of Denmark.