Optimal choice and allocation of distributed generations using evolutionary programming

Abstract

In this paper, evolutionary programming (EP) is proposed to determine the optimal choice and allocation of multi-type distributed generations (DG) to enhance power transfer capability and minimize system power losses of power transactions between source and sink areas in power systems. The optimal allocation includes the optimal type, size, and location. Two types of DG including photovoltaic (PV) and wind turbine (WT) are used in this study. The objective function is formulated as maximizing the benefit to cost ratio. The benefit means increasing in total transfer capability (TTC) with deducting system losses while the costs are the investment and operating costs of the selected DG units. Power transfer capability determinations are calculated based on the optimal power flow (OPF) technique. Test results on the modified IEEE 30-bus system show that the proposed EP can determine the optimal choice and allocation of DG to achieve the best TTC in the power system with the highest benefit to cost ratio.