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Article RSE 14008018

Mathematical Programming bounds for Large-Scale Unit Commitment Problems in Medium-Term Energy System Simulations


OASIcs 978-3-939897-67-5 , vol. 37, pp. 63-75, Agosto-2014.

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A. Ceselli (Università degli studi di Milano), A. Taverna (Università degli studi di Milano), A. Gelmini (RSE SpA) , G. Righini (Università degli studi di Milano)

EVOLRETE 2014 - Evolution and planning of the national electric system

We present algorithms and mathematical models developed to solve the dispatching and commitment problems of thermoelectric plants, which represent a mixed-integer linear problem (MILP) whose size makesit impractical to be solved directly by a commercial MILP solver.

We consider a large-scale unit commitment problem arising in medium-term simulation of energy networks, stemming from a joint project between the University of Milan and a major energy research centre in Italy. Optimal plans must be computed for a set of thermal and hydroelectric power plants, located in one or more countries, over a time horizon spanning from a few months to one year, with a hour-by-hour resolution. We propose a mixed-integer linear programming model for the problem.

Since the complexity of this unit commitment problem and the size of real-world instances make it impractical to directly optimise this model using general purpose solvers, we devise ad-hoc heuristics and relaxations to obtain approximated solutions and quality estimations.We exploit an incremental approach: at first, a linear relaxation of an aggregated model is solved. Then, the model is disaggregated and the full linear relaxation is computed.

Finally, a tighter linear relaxation of an extended formulation is obtained using column generation. At each stage, matheuristics are run to obtain good integer solutions. Experimental tests on real-world data reveal that accurate results can be obtained by our framework in affordable time, making it suitable for efficient scenario simulations.

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