Optimal Site and Size of DG with different Load Models using Cuckoo Search Algorithm

Abstract

Optimal set up of Distributed Generation (DG) resource in a distribution system with different objectives is a crucial requirement in the deregulated power market environment. A multi-objective optimization approach considering both technical and economic benefits with practical load models needs to be analyzed. Therefore, in this paper active and reactive power loss minimization, voltage stability index (VSI) improvement, as well as DGs installation cost, are used to formulate the multi-objective function (MOF). Voltage dependent real and reactive power loads are modeled to have practical results. To find the optimal site and size of multiple DGs in a distribution network, a brood parasitic breeding behavior based meta-heuristic Cuckoo Search Algorithm (CSA) is implemented. To investigate the effect of five different types of load models, the IEEE 33-bus radial distribution network is considered as a test system. Change in optimal size and location of DG with different voltage dependent load models are examined. To validate the effectiveness of the proposed methodology, a comparison is made with Particle Swarm optimization (PSO) and Genetic Algorithm (GA). Simulation results verify the efficacy of the proposed approach.