On Mixed-Integer Programming Formulations for the Unit Commitment Problem
Abstract
We provide a comprehensive overview of mixed-integer programming formulations for the unit commitment (UC) problem. UC formulations have been an especially active area of research over the past 12 years due to their practical importance in power grid operations, and this paper serves as a capstone for this line of work. We additionally provide publicly available reference implementations of all formulations examined. We computationally test existing and novel UC formulations on a suite of instances drawn from both academic and real-world data sources. Driven by our computational experience from this and previous work, we contribute some additional formulations for both generator production upper bounds and piecewise linear production costs. By composing new UC formulations using existing components found in the literature and new components introduced in this paper, we demonstrate that performance can be significantly improved—and in the process, we identify a new state-of-the-art UC formulation.
- Authors:
-
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Discrete Math & Optimization
- Univ. of Tennessee, Knoxville, TN (United States). Industrial and Systems Engineering
- Sandia National Lab. (SNL-CA), Livermore, CA (United States). Data Science & Cyber Analytics
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE Office of Electricity (OE); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1670724
- Report Number(s):
- SAND-2019-13440J
Journal ID: ISSN 1091-9856; 681098
- Grant/Contract Number:
- AC04-94AL85000; SC0018175; NA0003525
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- INFORMS Journal on Computing
- Additional Journal Information:
- Journal Volume: 32; Journal Issue: 4; Journal ID: ISSN 1091-9856
- Publisher:
- INFORMS
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Knueven, Bernard, Ostrowski, James, and Watson, Jean-Paul. On Mixed-Integer Programming Formulations for the Unit Commitment Problem. United States: N. p., 2020.
Web. doi:10.1287/ijoc.2019.0944.
Knueven, Bernard, Ostrowski, James, & Watson, Jean-Paul. On Mixed-Integer Programming Formulations for the Unit Commitment Problem. United States. https://doi.org/10.1287/ijoc.2019.0944
Knueven, Bernard, Ostrowski, James, and Watson, Jean-Paul. 2020.
"On Mixed-Integer Programming Formulations for the Unit Commitment Problem". United States. https://doi.org/10.1287/ijoc.2019.0944. https://www.osti.gov/servlets/purl/1670724.
@article{osti_1670724,
title = {On Mixed-Integer Programming Formulations for the Unit Commitment Problem},
author = {Knueven, Bernard and Ostrowski, James and Watson, Jean-Paul},
abstractNote = {We provide a comprehensive overview of mixed-integer programming formulations for the unit commitment (UC) problem. UC formulations have been an especially active area of research over the past 12 years due to their practical importance in power grid operations, and this paper serves as a capstone for this line of work. We additionally provide publicly available reference implementations of all formulations examined. We computationally test existing and novel UC formulations on a suite of instances drawn from both academic and real-world data sources. Driven by our computational experience from this and previous work, we contribute some additional formulations for both generator production upper bounds and piecewise linear production costs. By composing new UC formulations using existing components found in the literature and new components introduced in this paper, we demonstrate that performance can be significantly improved—and in the process, we identify a new state-of-the-art UC formulation.},
doi = {10.1287/ijoc.2019.0944},
url = {https://www.osti.gov/biblio/1670724},
journal = {INFORMS Journal on Computing},
issn = {1091-9856},
number = 4,
volume = 32,
place = {United States},
year = {2020},
month = {6}
}
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Works referencing / citing this record:
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A New Affinely Adjustable Robust Model for Security Constrained Unit Commitment under Uncertainty
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