Optimal power flow of two-terminal HVDC systems using backtracking search algorithm

• OPF of two-terminal HVDC systems is solved by using backtracking search algorithm (BSA).
• BSA is a population based evolutionary algorithm (EA).
• The proposed method is tested on three different IEEE test systems.
• The results by BSA are compared with those by ABC algorithm, GA, and the numerical method.
• The production costs and CPU times by BSA are less than those by the other methods.

This paper presents a solution technique for optimal power flow (OPF) of high-voltage direct current (HVDC) power systems using a backtracking search algorithm (BSA). BSA is a population-based evolutionary algorithm (EA), and it is not sensitive to initial conditions, contrary to most other meta-heuristic algorithms. The proposed algorithm is applied to three different test systems as follows: the modified 5-bus test system, the modified WSCC 9-bus test system, and the modified New England 39-bus test system. As a result of the simulations, minimum, maximum, and average production costs and CPU times are obtained for different cases of each of the three test systems. These results are also compared to those of the Artificial Bee Colony (ABC) algorithm, the Genetic Algorithm (GA), and the unified method provided in literature. In regard to the comparative results, it can be said that the proposed method has a shorter CPU time and is more efficient than the others. Thus, the applicability and efficiency of the proposed method in this field are demonstrated.