Multi-objective placement and sizing of DGs in distribution networks ensuring transient stability using hybrid evolutionary algorithm

Distributed generation (DG) units are increasing their popularity around the world. Considering the low inertia constant of DGs, the transient stability of them in the network is one of the major issues. In this paper, a new Pareto-based multi-objective problem is proposed for the placement and sizing of multiple micro-turbines in a distribution network to improve the transient stability index in addition to the losses and voltage profile. To calculate the transient stability index, the rates of fault occurrence in the different locations are considered. Also, the loads are modeled as both constant power and voltage dependent cases. In order to identify Pareto optimal solutions of the optimization problem, a novel hybrid evolutionary algorithm based on the Particle Swarm Optimization (PSO) and Shuffled Frog-Leaping (SFL) algorithm is presented. A 33-bus distribution test system is used to demonstrate the performance of the proposed method in DIgSILENT® PowerFactory software which can be used for practical applications in power systems.