Comparing Efficiency of PSO with GA in Transmission Expansion Planning Considering Network Adequacy

The lines adequacy of the network is necessary to provide load demands when the network is expanding, because its lack caused by load interruption. In this paper, in order to take the transmission lines condition after expansion into account from the line loading view points, the adequacy of the transmission network is considered for the solution of the STNEP problem. To obtain the optimal network arrangement, a discrete particle swarm optimization (DPSO) algorithm is being used for minimizing the network construction and operational cost and compared with genetic algorithm (GA). The particle swarm optimization is a recently developed evolutionary algorithm based on the swarm behavior in the nature and has a strong ability to find the most optimistic results. The motivation for using the DPSO technique is to reduce design effort and find an optimum planning network. The effectiveness of the proposed idea is tested on the Garver's six-bus network and an actual transmission network of the Azerbaijan regional electric company in Iran. The evaluation results evaluation reveals that the annual worth of the network adequacy has a considerable effect on the network arrangement. In addition, the obtained network, based on the DPSO algorithm, has lower investment cost and higher adequacy rate. To verify the results, expansion cost index on adequacy rate for IEEE Garvers network has been compared with GA results. Key-Words: DPSO, GA, STNEP, Network adequacy, Optimization problem, Transmission lines.