Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

Reactive Power Optimization Simulation of Active Distribution Network Based on Particle Swarm Optimization

Authors
Hao Zhang, Hongjuan Li, Min Xu
Corresponding Author
Hao Zhang
Available Online November 2017.
DOI
10.2991/amms-17.2017.61How to use a DOI?
Keywords
active distribution network; mathematical model; particle swarm algorithm; simulation
Abstract

The access of a large number of renewable energy makes the active distribution network become the inevitable trend of development, coordination of renewable distributed power and traditional reactive power compensation device can effectively achieve the active distribution network reactive power optimization. The simulation results of IEEE33 node system show that the mathematical model is correct and accurate for the reactive power optimization of the distribution network, and the particle swarm optimization algorithm can effectively search the global optimal.

Copyright
© 2017, 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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Volume Title
Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
Series
Advances in Intelligent Systems Research
Publication Date
November 2017
ISBN
978-94-6252-433-0
ISSN
1951-6851
DOI
10.2991/amms-17.2017.61How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - CONF
AU  - Hao Zhang
AU  - Hongjuan Li
AU  - Min Xu
PY  - 2017/11
DA  - 2017/11
TI  - Reactive Power Optimization Simulation of Active Distribution Network Based on Particle Swarm Optimization
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 272
EP  - 275
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.61
DO  - 10.2991/amms-17.2017.61
ID  - Zhang2017/11
ER  -