Abstract
This paper presents a hybrid column-and-constraint-generation augmented-Lagrangian algorithm to efficiently solve the robust security-constrained dynamic transmission expansion planning (TEP) problem. The column-and-constraint generation algorithm separates the TEP problem into a master problem and a set of subproblems decomposable by time period. Additionally, the computationally expensive master problem is decomposed into three computationally efficient sub-master problems: an upper-master quadratic problem, a middle-master quadratic unconstrained binary problem, and a lower-master quadratic unconstrained problem. A set of auxiliary variables are used to relax as real ones the binary variables corresponding to the status of candidate transmission lines enabling the master problem decomposition. The solutions of the three sub-master problems are coordinated using a three-block alternating direction method of multipliers algorithm to enforce binary variables to be binary. An initialization strategy based on load shedding is used to enhance the performance of the proposed algorithm. Simulation results on the IEEE 118-bus test system show the efficient performance of the proposed algorithm for solving security-constrained dynamic TEP problems.
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