Exploiting Identical Generators in Unit Commitment
- Univ. of Tennessee, Knoxville, TN (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Here, 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 induced 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 operator 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 computational difficulty.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of Tennessee, Knoxville, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Workforce Development for Teachers and Scientists (WDTS); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- Grant/Contract Number:
- AC04-94AL85000; SC0018175
- OSTI ID:
- 1421648
- Alternate ID(s):
- OSTI ID: 2339861
- Report Number(s):
- SAND-2018-0031J; 659726
- Journal Information:
- IEEE Transactions on Power Systems, Vol. 33, Issue 4; ISSN 0885-8950
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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