Using a Modified Shuffled Frog Leaping Algorithm (MSFLA) in Locating and Determining the Optimal Capacity of Distributed Generation Units

Restructuring the power systems and the simultaneous trend to renewable resources has increased the importance of appropriate planning of distribution companies to maximize the potential of distributed resources. Therefore, due to the growing trend of using distributed generations, it is necessary to determine the location and optimal capacity and examine the effects of these units on the power system, especially in the distribution network. Distributed generation sources can be a source of positive impacts, such as improving the technical parameters of the network, including losses, voltage profiles, reliability, and congestion reduction in the power systems, according to the specifications, operating conditions and installation location. In this paper, improvement of the profile and reduction of the losses is used as an object and through appropriate weight coefficients in an object function for the purpose of placement and determining the optimal capacity of the distributed generation sources. In the proposed method the Modified Shuffled Frog Leaping Algorithm (MSFLA) is implemented on an IEEE 33-bus standard network. Also, simulation results are compared with GA and PSO algorithms on the network, which clearly shows the efficiency of the proposed method in the placement and determining the optimal capacity of the distributed generation sources