The Unit Commitment Problem (UCP) aims at finding the optimal commitment for a set of thermal power plants in a Power System (PS) according to some criterion. Our work stems from a collaboration with RSE S.p.A., a major industrial research centre for PSs in Italy. In this context the UCP is formulated as a large-scale MILP spanning countries over a year with hourly resolution to simulate the ideal behaviour of the system in different scenarios. Our goal is to refine existing heuristic solutions to increase simulation reliability. In our previous studies we devised a Column Generation algorithm (CG) which, however, shows numerical instability due to degeneracy in the master problem. Here we evaluate the application of Benders Decomposition (BD), which yields better conditioned subproblems. We also employ Magnanti-Wong cuts and a "two-phases scheme", which first quickly computes valid cuts by applying BD to the continuous relaxation of the problem and then restores integrality. Experimental results on weekly instances for the Italian system show the objective function to be flat. Even if such a feature worsens convergence, the algorithm is able to reach almost optimal solutions in few iterations.

Benders Decomposition on Large-Scale Unit Commitment Problems for Medium-Term Power Systems Simulation / A. Taverna (OPERATIONS RESEARCH PROCEEDINGS). - In: Operations Research Proceedings 2016 / [a cura di] A. Fink, G. Fügenschuh, M. J. Geiger. - Prima edizione. - [s.l] : Springer, 2018. - ISBN 978-3-319-55701-4. - pp. 179-184 (( convegno OR Hamburg 2016 - International Conference On Operations Research - Analytical Decision Making tenutosi a Hamburg nel 2016 [10.1007/978-3-319-55702-1_25].

Benders Decomposition on Large-Scale Unit Commitment Problems for Medium-Term Power Systems Simulation

A. Taverna
Primo
2018

Abstract

The Unit Commitment Problem (UCP) aims at finding the optimal commitment for a set of thermal power plants in a Power System (PS) according to some criterion. Our work stems from a collaboration with RSE S.p.A., a major industrial research centre for PSs in Italy. In this context the UCP is formulated as a large-scale MILP spanning countries over a year with hourly resolution to simulate the ideal behaviour of the system in different scenarios. Our goal is to refine existing heuristic solutions to increase simulation reliability. In our previous studies we devised a Column Generation algorithm (CG) which, however, shows numerical instability due to degeneracy in the master problem. Here we evaluate the application of Benders Decomposition (BD), which yields better conditioned subproblems. We also employ Magnanti-Wong cuts and a "two-phases scheme", which first quickly computes valid cuts by applying BD to the continuous relaxation of the problem and then restores integrality. Experimental results on weekly instances for the Italian system show the objective function to be flat. Even if such a feature worsens convergence, the algorithm is able to reach almost optimal solutions in few iterations.
No
English
unit commitment, power systems, mixed integer linear programming, Benders decomposition, large scale optimization
Settore MAT/09 - Ricerca Operativa
Intervento a convegno
Comitato scientifico
Ricerca applicata
Pubblicazione scientifica
Operations Research Proceedings 2016
A. Fink, G. Fügenschuh, M. J. Geiger
Prima edizione
Springer
2018
24-mag-2017
179
184
6
978-3-319-55701-4
978-3-319-55702-1
Volume a diffusione internazionale
OR Hamburg 2016 - International Conference On Operations Research - Analytical Decision Making
Hamburg
2016
German Operations Research Society, GOR e. V.
Convegno internazionale
Intervento inviato
https://www.springer.com/it/book/9783319557014#otherversion=9783319557014
NON aderisco
A. Taverna
Book Part (author)
none
273
Benders Decomposition on Large-Scale Unit Commitment Problems for Medium-Term Power Systems Simulation / A. Taverna (OPERATIONS RESEARCH PROCEEDINGS). - In: Operations Research Proceedings 2016 / [a cura di] A. Fink, G. Fügenschuh, M. J. Geiger. - Prima edizione. - [s.l] : Springer, 2018. - ISBN 978-3-319-55701-4. - pp. 179-184 (( convegno OR Hamburg 2016 - International Conference On Operations Research - Analytical Decision Making tenutosi a Hamburg nel 2016 [10.1007/978-3-319-55702-1_25].
info:eu-repo/semantics/bookPart
1
Prodotti della ricerca::03 - Contributo in volume
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/469592
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