Transmission expansion planning is receiving an increased attention, primarily due to the large-scale grid upgrades that will be necessary to accommodate renewable generation or to increase cross-border capacity. The intermittency of renewables, and the uncertainties inherent to long-term planning, makes it advisable to use solution methods that cope with uncertainty explicitly. Stochastic Optimisation and, in particular, Benders’ decomposition, is one of the most widely applied approaches in this context. However, large-scale planning can still present computational problems. Several techniques have been proposed to accelerate Benders’ decomposition. However, they appear disperse and usually without a clear application scope. Most of them have not been applied to TEP yet. This study presents a comprehensive view on TEP applied to Benders’ decomposition and the techniques available to accelerate its resolution, together with semi-relaxed cuts, a technique proposed in the previous work by Lumbreras and Ramos in 2013. Then, for three case studies based on IEEE test cases, the most promising of these techniques are implemented and their effectiveness is compared. All test cases could save about 50% of solution time using simple and easy-to-implement techniques, showing that there is an interest in using these approaches in academic and practical TEP applications.