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Exploiting Identical Generators in Unit Commitment

Ben Knueven (bknueven***at***vols.utk.edu)
Jim Ostrowski (jostrows***at***utk.edu)
Jean-Paul Watson (jwatson***at***sandia.gov)

Abstract: We present sufficient conditions under which thermal generators can be aggregated in mixed-integer linear programming (MILP) formulations of the unit commitment (UC) problem, while maintaining feasibility and optimality for the original disaggregated problem. Aggregating thermal generators with identical characteristics (e.g., minimum/maximum power output, minimum up/down-time, and cost curves) into a single unit reduces redundancy in the search space caused by both exact symmetry (permutations of generator schedules) and certain classes of mutually non-dominated solutions. We study the impact of aggregation on two large-scale UC instances, one from the academic literature and another based on real-world data. Our computational tests demonstrate that when present, identical generators can negatively affect the performance of modern MILP solvers on UC formulations. Further, we show that our reformation of the UC MILP through aggregation is an effective method for mitigating this source of difficulty.

Keywords: Mixed-integer linear programming (MILP), unit commitment (UC), symmetry

Category 1: Applications -- OR and Management Sciences (Scheduling )

Category 2: Integer Programming ((Mixed) Integer Linear Programming )

Citation: University of Tennessee, June 2017

Download: [PDF]

Entry Submitted: 06/30/2017
Entry Accepted: 06/30/2017
Entry Last Modified: 06/30/2017

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