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Global Solution Strategies for the Network-Constrained Unit Commitment Problem With AC Transmission Constraints

Jianfeng Liu (liu1172***at***purdue.edu)
Anya Castillo (arcasti***at***sandia.gov)
Jean-Paul Watson (jwatson***at***sandia.gov)
Carl Laird (cdlaird***at***sandia.gov)

Abstract: We propose a novel global solution algorithm for the network-constrained unit commitment problem that incorporates a nonlinear alternating current 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 and leverage second-order cone relaxations, piecewise outer approximations, and optimization-based bounds tightening to provide 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.

Keywords: Unit commitment, AC transmission models, multi-tree optimization

Category 1: Global Optimization

Category 2: Integer Programming

Category 3: Nonlinear Optimization

Citation: Jianfeng Liu, Carl D. Laird, Joseph K. Scott, Jean-Paul Watson, and Anya Castillo. Global Solution Strategies for the Network-Constrained Unit Commitment Problem With AC Transmission Constraints. IEEE Transactions on Power Systems.

Download: [PDF]

Entry Submitted: 11/11/2016
Entry Accepted: 12/01/2016
Entry Last Modified: 11/21/2018

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