Optimal Distributed Generation Allocation and Sizing Using Genetic and Ant Colony Algorithms

Abstract

Distributed generators (DG) which installed into distribution network to face the increasing of load demand. DG can used to enhance power generation systems and improve distribution network efficiency. However, the distributed generators units’ implementation at not convenient position and sizing can lead to negative impacts such as a growing in power losses and invasion of system constraints. Because the rising of demand in energy. The appropriate placement and sizing of DG’s units is a credible solution to much problems in distribution system, for example power loss reduction and voltage regulation. The allocation of distributed generators into the distribution network can significantly impact in the transmission and distribution systems. Therefore, a method, which can identify an optimum DG location and size, is necessary. In this paper, Genetic Algorithm (GA) and Ant colony Algorithm (ACO) optimization techniques are proposed to find optimal sizing and location for distributed generation in electrical networks. The objective function of the work relies upon a linearized model to compute the active power losses as a function of power supplied from the generators. This strategy based on a strong coupling between active power and power flow taking into consideration the voltage angles. With the end goal to exhibit the adequacy of the proposed method, the proposed strategy is applied on IEEE 57-bus standard systems. Different maximum penetration level capacity of DG units and various possible places of DG units among several types of DG (active, reactive or active and reactive power) are considered. Results show that the optimization tools employing GA and ACO are effective in reducing active power losses by finding the optimal placement and sizing of DG units