The Approach of Genetic Algorithms Application on Reactive Power Optimization of Electric Power Systems

DOI

10.2991/macmc-17.2018.45How to use a DOI?

Keywords

Electric Power Systems; Genetic Algorithms; Reactive Power Optimization

Abstract

With the rapid growth of China's economy and the development of industry, the demand of power quality in various departments of national economy is more and more strict. In the power system, reactive power plays a special role. The research on reactive power optimization of power system has significant practical significance for reducing the extra active power consumption and improving the voltage operation level caused by the unreasonable allocation of reactive power. Using the improved genetic algorithm proposed in this paper, the standard test system is used to simulate the reactive power optimization, and the optimization results of the simple genetic algorithm and the improved genetic algorithm are compared. The simulation results show that the proposed algorithm is feasible and effective, and the improved genetic algorithm has lower active network loss and better global convergence performance and convergence speed.

Copyright

© 2018, 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  - RuiJin Zhu
PY  - 2018/01
DA  - 2018/01
TI  - The Approach of Genetic Algorithms Application on Reactive Power Optimization of Electric Power Systems
BT  - Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)
PB  - Atlantis Press
SP  - 206
EP  - 210
SN  - 2352-5401
UR  - https://doi.org/10.2991/macmc-17.2018.45
DO  - 10.2991/macmc-17.2018.45
ID  - Zhu2018/01
ER  -