An aggregated multi-cut decomposition algorithm for two-stage transmission expansion planning problems

The L-shaped method is a decomposition algorithm that is commonly used to solve large-scale two-stage stochastic programming problems. The classic single-cut L-shaped method usually suffer the performance issue because only a single optimality cut is applied at each major iteration. This paper presents an aggregated multi-cut version of the L-shaped method for solving two-stage transmission expansion planning (TEP) problems. This algorithm allows the user to control the aggregation level of the optimality cuts so that the overall computational performance can be improved. Simulation results show that the proposed algorithm is computationally more efficient than the classical L-shaped method.