Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints
- Purdue Univ., West Lafayette, IN (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Clemson Univ., Clemson, SC (United States)
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.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- Grant/Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1485467
- Report Number(s):
- SAND-2018-11995J; 668931
- Journal Information:
- IEEE Transactions on Power Systems, Vol. 34, Issue 2; ISSN 0885-8950
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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