DocumentCode
135903
Title
Swarm intelligence based multi-phase OPF for peak power loss reduction in a smart grid
Author
Anwar, Ayesha ; Mahmood, Abdun Naser
Author_Institution
Univ. of New South Wales, Canberra, ACT, Australia
fYear
2014
fDate
27-31 July 2014
Firstpage
1
Lastpage
5
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.
Keywords
distributed power generation; load flow; particle swarm optimisation; power distribution planning; smart power grids; swarm intelligence; DG capacity planning; IEEE 8500-node benchmark distribution system; balanced networks; computational intelligence; constriction factor; cosimulation framework; multiphase distribution networks; optimal power flow tool; particle swarm optimization; peak power loss reduction; reactive power compensation devices; smart grid; swarm intelligence based multiphase OPF; unbalanced loadings; voltage control; Genetic algorithms; Optimization; Particle swarm optimization; Power system stability; Smart grids; Voltage control; 8500 node test system; CF-PSO; Co-simulation; Smart grid; Unbalanced multi-phase OPF;
fLanguage
English
Publisher
ieee
Conference_Titel
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location
National Harbor, MD
Type
conf
DOI
10.1109/PESGM.2014.6939824
Filename
6939824
Link To Document