An improved hybrid approach for the simultaneous allocation of distributed generators and time varying loads in distribution systems

Abstract

Distributed Generation (DG) studies are generally conducted considering a single type of DG units integrated with the Distribution System (DS). However, these studies may not evaluate optimum benefits offered by the DG integration. This paper presents a novel framework for individual and simultaneous allocation of different types of DG units in DS while considering varying load demand and probabilistic generation of DG units. A Salp Swarm Algorithm (SSA) and Particle Swarm Optimization (PSO) based new hybrid method that utilizes a single controlling parameter is proposed for simultaneous allocation of DG units, aiming to minimize a multi-objective index. The strength of the proposed SSA-PSO hybrid approach is validated on seventeen benchmark functions and the performance of the novel framework for optimal allocation of DG units is validated through implementation on the 69-bus system. The results demonstrate that the proposed hybrid approach performs better as compared to other meta-heuristics techniques. Moreover, simultaneous allocation significantly reduces the multi-objective index as compared to individual DG units’ integration.

Keywords

• Optimal allocation
• Metaheuristics
• Distributed generation
• Multi-objective index