A Combinatorial Method for Transmission Expansion Planning

This paper proposes an efficient and novel method for transmission expansion planning in regulated environment of power systems. The method is based on combination of two algorithms such as special genetic algorithm (GA) and constructive heuristic algorithm. The proposed GA has its own special characteristics that make it better than other metahuristic methods in transmission expansion planning problems. The improvement phase is the main characteristic that makes this type of GA more efficient. It means that if after mating procedure (selection, crossover and mutation), the offspring was an infeasible one, by using a suitable constructive heuristic algorithm, and the aforementioned offspring is changed to a feasible one. Also by using a relaxed linear model of TEP and importing cost perturbation, a qualified initial population is obtained and used as an initial population of GA. The simulation results obtained from the proposed method were compared to those achieved from previous literature in terms of solution quality and computational efficiency. Results reveal that the superiority of this method in both aspects of financial and CPU time.