Application of Improved Quantum Genetic Algorithm on Reactive Power Optimization

YANG Jia-jun; XU Jian-zheng

doi:10.14044/j.1674-1757.pcrpc.2013.04.006

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Application of Improved Quantum Genetic Algorithm on Reactive Power Optimization

更新时间：2024-09-14

- Application of Improved Quantum Genetic Algorithm on Reactive Power Optimization
- POWER CAPACITOR & REACTIVE POWER COMPENSATION Vol. 34, Issue 4, Pages: 15-20(2013)
- 作者机构：
  
  山东大学电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.14044/j.1674-1757.pcrpc.2013.04.006
  CLC： TM714.3
- Published：2013，
- 稿件说明：
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[1]杨佳俊,徐建政.改进量子遗传算法在无功优化中的应用[J].电力电容器与无功补偿,2013,34(04):15-20.

YANG JIA-JUN, XU JIAN-ZHENG. Application of Improved Quantum Genetic Algorithm on Reactive Power Optimization. [J]. Power capacitor & reactive power compensation, 2013, 34(4): 15-20.
[1]杨佳俊,徐建政.改进量子遗传算法在无功优化中的应用[J].电力电容器与无功补偿,2013,34(04):15-20. DOI： 10.14044/j.1674-1757.pcrpc.2013.04.006.

YANG JIA-JUN, XU JIAN-ZHENG. Application of Improved Quantum Genetic Algorithm on Reactive Power Optimization. [J]. Power capacitor & reactive power compensation, 2013, 34(4): 15-20. DOI： 10.14044/j.1674-1757.pcrpc.2013.04.006.

摘要

在传统的无功优化模型中引入静态电压稳定指标

建立以网损最小的优化模型。量子遗传算法（quantum genetic algorithm

QGA）将量子的态矢量引入遗传编码

将量子比特的几率幅表示应用于染色体的编码

实现染色体的演化

效果比常规遗传算法要好。常规量子算法中的量子门角度的选取决定着进化的速度和方向

也影响着最终的优化效果

本文提出一种改进的量子旋转门算法

它能够自适应地计算旋转角度

能够提高全局的搜索能力

缩减搜索代数

加快搜索速度

同时避免陷入局部最优

之后采用IEEE14节点和IEEE 30节点进行验证

取得了较好的效果。

Abstract

Static voltage stability index is introduced in the traditional reactive power optimization model to set up an optimization model with minimum loss.Quantum genetic algorithm（QGA） is to introduce quantum state vector into genetic code.Quantum bit probability amplitude is applied to chromosome coding to achieve evolution of the chromosome and the effect is better than the conventional algorithm

but the evolution speed and direction are determined by the selection of the quantum gate angle in conventional quantum algorithm and the final optimization effect is affected by it.In this paper

an improved quantum rotation gate algorithm is proposed which can adaptively compute the rotation angle

improve the global search ability

reduce search algebra

speed up the search speed and

at the same time

avoid falling into local optimum.Then

it is verified with IEEE 14 and IEEE 30 nodes with better result.

关键词

无功优化电力系统量子遗传算法（QGA）量子旋转门

Keywords

reactive power optimizationpower systemquantum genetic algorithm（QGA）quantum rotation gate

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