Swarm Intelligence Based Multi-phase OPF For Peak Power Loss Reduction In A Smart Grid

TL;DR

This paper introduces a novel multi-phase optimal power flow method using swarm intelligence to reduce peak power losses in unbalanced smart grid distribution networks.

Contribution

It proposes a new OPF technique based on particle swarm optimization tailored for unbalanced multi-phase distribution systems, addressing a research gap.

Findings

Effective reduction in peak power losses demonstrated

Validated on IEEE 8500-node benchmark system

Improved power flow management in unbalanced networks

Abstract

Recently there has been increasing interest in improving smart grids efficiency using computational intelligence. A key challenge in future smart grid is designing Optimal Power Flow tool to solve important planning problems including optimal DG capacities. Although, a number of OPF tools exists for balanced networks there is a lack of research for unbalanced multi-phase distribution networks. In this paper, a new OPF technique has been proposed for the DG capacity planning of a smart grid. During the formulation of the proposed algorithm, multi-phase power distribution system is considered which has unbalanced loadings, voltage control and reactive power compensation devices. The proposed algorithm is built upon a co-simulation framework that optimizes the objective by adapting a constriction factor Particle Swarm optimization. The proposed multi-phase OPF technique is validated using IEEE 8500-node benchmark distribution system.