Reactive Power Optimization of Power System Based on Phasor Particle Swarm Optimization

doi:10.13438/j.cnki.jdzk.2020.04.006

Abstract

Abstract:

Reactive power optimization of power system can reduce active power loss and ensure the safety and economy of operation. Phasor particle swarm optimization (PPSO) is used to solve the problem of reactive optimizationin power system. The phase angle obtained through initialization is introduced into the speed updating process to improve the searching accuracy. In IEEE-14 node system, reactive optimization simulation experiments are conducted through PPSO algorithm, standard particle swarm optimization algorithm, stochastic inertia weighted particle swarm optimization algorithm, improved attractive repulsive particle swarm optimization algorithm. The simulation results show that PPSO can better reduce the active power loss.

Key words: phasor particle swarm optimization, power system, reactive power optimization, active power loss

WANG Lin. Reactive Power Optimization of Power System Based on Phasor Particle Swarm Optimization[J]. Journal of Jishou University（Natural Sciences Edition), DOI: 10.13438/j.cnki.jdzk.2020.04.006.

References

[1] 王凌谊，候世英，吕厚余，等. 电力系统无功优化与无功补偿[J].电气应用,2006，25(10):45-48.
[2] 肖定垚，王承民，曾平良，等. 电力系统灵活性及其评价综述[J].电网技术,2014，38(06):1569-1576
[3] 刘哲，赵冬梅，张旭.基于混沌蚁群算法的电力系统无功优化[J].现代电力，2009，26(4):15-19.
[4] HOBSON ERIC. Network Constrained Reactive Power Control Using Linear Programming[J]. IEEE Transactions on Power Apparatus and Systems, 1980, 99(3): 868-877.
[5] BURCHETT R C, HAPP H H, VIERATH D R. Quadratically Convergent Optimal Power Flow[J]. IEEE Transactions on Power Apparatus and Systems, 1984, 103(11): 3267-3275.
[6] 张鹏,刘玉田.配电系统电压控制和无功优化的简化动态规划法[J].电力系统及其自动化学报，1999,11(4): 49-53.
[7] 杨艳玲，冯林桥，刘金玲.改进遗传算法在配电网无功优化的应用[J].吉首大学学报(自然科学版)，2008,29(5)：68-71.
[8] 王勇，杨月红，晁光，等.基于改进扩大邻域禁忌搜索算法的电力系统无功优化[J].陕西电力，2014,42(3)：24-26;31.
[9] 陆景，庹先国，彭桂力.基于粒子群算法的电力系统无功优化[J].微型机与应用，2017,36(13)：19-21;25.
[10] 李丽，牛奔.粒子群优化算法[M].北京: 冶金工业出版社, 2009:40.
[11] PANT M, RADHA T, SINGH V P. A Simple Diversity Guided Particle Swarm Optimization[C]. 2007 IEEE Congress on Evolutionary Computation. Singapore: IEEE, 2007: 3294-3299.
[12] GHASEMI MOJTABA, AKBARI EBRAHIM, RAHIMNEJAD ABOLFAZL, et al. Phasor Particle Swarm Optimization: A Simple and Efficient Variant of PSO[J]. Soft Computing, 2018,23(4): 9701-9718.
[13] 王志宁，李辛琦，冯成铭.基于改进蚁群算法的电网无功补偿优化控制研究[J].磁性材料及器件，2010,41(6):29-31;35.
[14] 徐雷.基于改进粒子群算法的电力系统无功优化[D].成都：西华大学，2016: 41-42.
[15] SHI Yuhui, EBERHART RUSSELL. A Modified Particle Swarm Optimizer[C]// IEEE World Congress on Computational Intelligence, 1998 IEEE International Conference on Evolutionary Computation. USA, Anchorage: IEEE, 1998: 69-73.