Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints
Abstract
Here, we propose a novel global solution algorithm for the network-constrained unit commitment problem that incorporates a nonlinear alternating current (AC) model of the transmission network, which is a nonconvex mixed-integer nonlinear programming (MINLP) problem. Our algorithm is based on the multi-tree global optimization methodology, which iterates between a mixed-integer lower-bounding problem and a nonlinear upper-bounding problem. We exploit the mathematical structure of the unit commitment problem with AC power flow constraints (UC-AC) and leverage second-order cone relaxations, piecewise outer approximations, and optimization-based bounds tightening to guarantee a globally optimal solution at convergence. Numerical results on four benchmark problems illustrate the effectiveness of our algorithm, both in terms of convergence rate and solution quality.
- Authors:
-
- Purdue Univ., West Lafayette, IN (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Clemson Univ., Clemson, SC (United States)
- 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 National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1485467
- Report Number(s):
- SAND-2018-11995J
Journal ID: ISSN 0885-8950; 668931
- Grant/Contract Number:
- AC04-94AL85000
- Resource Type:
- Accepted Manuscript
- Journal Name:
- IEEE Transactions on Power Systems
- Additional Journal Information:
- Journal Volume: 34; Journal Issue: 2; Journal ID: ISSN 0885-8950
- Publisher:
- IEEE
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 24 POWER TRANSMISSION AND DISTRIBUTION; Optimal Power Flow; Unit Commitment; Optimization methods; Power system modeling
Citation Formats
Liu, Jianfeng, Laird, Carl Damon, Scott, Joseph K., Watson, Jean -Paul, and Castillo, Anya. Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints. United States: N. p., 2018.
Web. doi:10.1109/TPWRS.2018.2876127.
Liu, Jianfeng, Laird, Carl Damon, Scott, Joseph K., Watson, Jean -Paul, & Castillo, Anya. Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints. United States. https://doi.org/10.1109/TPWRS.2018.2876127
Liu, Jianfeng, Laird, Carl Damon, Scott, Joseph K., Watson, Jean -Paul, and Castillo, Anya. Wed .
"Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints". United States. https://doi.org/10.1109/TPWRS.2018.2876127. https://www.osti.gov/servlets/purl/1485467.
@article{osti_1485467,
title = {Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints},
author = {Liu, Jianfeng and Laird, Carl Damon and Scott, Joseph K. and Watson, Jean -Paul and Castillo, Anya},
abstractNote = {Here, we propose a novel global solution algorithm for the network-constrained unit commitment problem that incorporates a nonlinear alternating current (AC) model of the transmission network, which is a nonconvex mixed-integer nonlinear programming (MINLP) problem. Our algorithm is based on the multi-tree global optimization methodology, which iterates between a mixed-integer lower-bounding problem and a nonlinear upper-bounding problem. We exploit the mathematical structure of the unit commitment problem with AC power flow constraints (UC-AC) and leverage second-order cone relaxations, piecewise outer approximations, and optimization-based bounds tightening to guarantee a globally optimal solution at convergence. Numerical results on four benchmark problems illustrate the effectiveness of our algorithm, both in terms of convergence rate and solution quality.},
doi = {10.1109/TPWRS.2018.2876127},
journal = {IEEE Transactions on Power Systems},
number = 2,
volume = 34,
place = {United States},
year = {Wed Oct 17 00:00:00 EDT 2018},
month = {Wed Oct 17 00:00:00 EDT 2018}
}
Web of Science
Figures / Tables:
Works referencing / citing this record:
A joint energy and reserve scheduling framework based on network reliability using smart grids applications
journal, July 2019
- Ansari, Javad; Malekshah, Soheil
- International Transactions on Electrical Energy Systems, Vol. 29, Issue 11
A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units
journal, September 2019
- Lin, Shunjiang; Fan, Guansheng; Lu, Yuan
- Energies, Vol. 12, Issue 19