Modified particle swarm optimisation with a novel initialisation for finding optimal solution to the transmission expansion planning problem

The transmission expansion planning (TEP) problem consists of determining when and where new circuits are needed and should be installed to serve the growing demand for electric power. TEP is a hard, large-scale, non-linear, mixed-integer and non-convex combinatorial problem. Finding the solution for the TEP problem is very difficult as the number of options to be analysed and compared increases exponentially with the size of the network. This study presents an application of the modified particle swarm optimisation technique, with a novel initialisation (population monitored for complementary magnitudes initialisation), for improved performance (in terms of success rate and convergence) to the highly complex TEP problem. Here, the DC model of the transmission network is considered. The success of the proposed methodology has been tested on the Garver 6-bus system, IEEE 24-bus system and Southern Brazilian 46-bus system and validated.