Sub-transmission sub-station expansion planning based on bacterial foraging optimization algorithm

In the recent years, significant research efforts have been devoted to the optimal planning of power systems. sub-station expansion panning (SEP), as a sub-system of power system planning, consists of finding the most economical solution with the optimal location and size of future sub-stations and/or feeders to meet the future load demand. The large number of design variables and combination of discrete and continuous variables make the sub-station expansion planning a very challenging problem. So far, various methods have been presented to solve such a complicated problem. Since the bacterial foraging optimization algorithm (BFOA) yield to proper results in power system studies, and it has not been applied to SEP in subtransmission voltage level problems yet, this paper develops a new BFO-based method to solve the subtransmission sub-station expansion planning (STSEP) problem. The technique discussed in this paper uses BFOA to simultaneously optimize the sizes and locations of both the existing and new installed sub-stations and feeders by considering reliability constraints. To clarify the capabilities of the proposed method, two test systems (a typical network and a real one) are considered, and the results of applying GA and BFOA to these networks are compared. The simulation results demonstrate that BFOA has the potential to find more optimal results than the other algorithms under the same conditions. Also the fast convergence and consideration of the real-world network limitations, as the problem constraints, and the simplicity in applying it to real networks are the main features of the proposed method.