A Novel Particle Swarm Algorithm Based Multi-agent for Coordinated Volt/Var Optimization

DOI

10.2991/icmia-16.2016.135How to use a DOI?

Keywords

Power system; Particle swarm algorithm; Multi-agent system; Coordinated volt/var optimization

Abstract

Coordinated volt/var optimization is fundamental to power dispatch and stability of power system, a novel particle swarm algorithm based multi-agent(MAPSO) is presented. The algorithm combines particle swarm optimization algorithm(PSO) with multi-agent system(MAS). The PSO-MAS utilize an agent as a particle to solve the optimization problem. Every agent lives in a fixed lattice with competition and cooperation by using its knowledge among neighbors. MAPSO integrates these agent-agent interactions and evolution mechanism of PSO to minimize the value of objective function. To test the performance of MAPSO for coordinated Volt/var optimization, simulation experiments were done on an IEEE 30-bus power system. The results show that MAPSO can converge to optimal solutions faster than many other approaches, and be applied to control volt/var to decrease the power loss and improve power quality.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiang Wang
AU  - Jun Chen
PY  - 2016/11
DA  - 2016/11
TI  - A Novel Particle Swarm Algorithm Based Multi-agent for Coordinated Volt/Var Optimization
BT  - Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmia-16.2016.135
DO  - 10.2991/icmia-16.2016.135
ID  - Wang2016/11
ER  -