基于改进教与学算法的含电能路由器的电力系统无功优化

doi:10.12204/j.issn.1000-7229.2022.06.012

电力建设 ›› 2022, Vol. 43 ›› Issue (6): 110-118.doi: 10.12204/j.issn.1000-7229.2022.06.012

基于改进教与学算法的含电能路由器的电力系统无功优化

从帆平(), 周建萍(), 茅大钧, 齐国庆, 黄祖繁

上海电力大学自动化工程学院,上海市 200090

收稿日期:2021-11-02 出版日期:2022-06-01 发布日期:2022-05-31
通讯作者: 周建萍 E-mail:992451774@qq.com;zhoujianping@shiep.edu.cn
作者简介:从帆平(1996),男,硕士研究生,主要研究方向为电力系统无功优化,E-mail:992451774@qq.com
茅大钧(1966),男,博士,教授,研究方向为电站过程自动化、计算机测控技术以及智能仪器仪表
齐国庆(1996),男,硕士研究生,主要研究方向为有源电力滤波器控制策略
黄祖繁(1998),男,硕士研究生,主要研究方向为电能质量调节器控制策略
基金资助:
国家自然科学基金资助项目(61275038);上海市“科技创新行动计划”地方院校能力建设专项(19020500700)

Reactive Power Optimization of Power System with Electric Energy Router Applying Modified Teaching-Learning Algorithm

CONG Fanping(), ZHOU Jianping(), MAO Dajun, QI Guoqing, HUANG Zufan

College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China

Received:2021-11-02 Online:2022-06-01 Published:2022-05-31
Contact: ZHOU Jianping E-mail:992451774@qq.com;zhoujianping@shiep.edu.cn
Supported by:
the National Natural Science Foundation of China(61275038);the Local Colleges and Universities Capacity Construction Project of Shanghai “Science and Technology Innovation Action Plan”(19020500700)

摘要/Abstract

摘要：

针对传统智能算法在求解计及电能路由器的电力系统无功优化模型时存在的收敛性和多样性问题,提出一种基于轮盘赌选择和自适应柯西变异策略的改进教与学算法,并应用于含电能路由器的电力系统无功优化。该算法在学习阶段引入轮盘赌选择法,提高群体的学习效率,在教学完成后引入自适应柯西变异策略,增强班级种群的多样性,避免迭代过程陷入局部最优解。然后,建立以有功网损和电压偏离度最小为目标函数的电力系统无功优化模型,并以修改后的IEEE RTS-79标准测试系统为算例进行仿真分析,结果表明改进后的算法兼顾了收敛性和多样性,相比于传统算法具有更好的优化效果。

关键词: 电能路由器(EER), 教与学优化算法, 轮盘赌选择, 自适应柯西变异, 无功优化

Abstract:

In this paper,an improved teaching and learning algorithm based on roulette wheel selection and adaptive Corsi variation strategy is proposed to solve the convergence and diversity problems of the traditional intelligent algorithm and it is applied to the reactive power optimization of power system with electric energy router (EER). The algorithm introduces roulette selection method in the learning phase to improve the learning efficiency of the group, and adopts adaptive Cauchy mutation strategy after the teaching to enhance the diversity of the class population, which avoids falling into local optimal solutions in the iterative process. Then, a reactive power optimization model is established with the objective function of minimizing active network loss and voltage deviation. The modified IEEE RTS-79 standard test system is used as an example for simulation analysis. The results show that the improved algorithm has both convergence and diversity, which has better optimization effect than the traditional algorithm.

Key words: electric energy router (EER), teaching-learning algorithm, roulette wheel selection, adaptive Cauchy mutation, reactive power optimization

中图分类号:

TM711

从帆平, 周建萍, 茅大钧, 齐国庆, 黄祖繁. 基于改进教与学算法的含电能路由器的电力系统无功优化[J]. 电力建设, 2022, 43(6): 110-118.

CONG Fanping, ZHOU Jianping, MAO Dajun, QI Guoqing, HUANG Zufan. Reactive Power Optimization of Power System with Electric Energy Router Applying Modified Teaching-Learning Algorithm[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(6): 110-118.

图/表 14

图1 电能路由器的通用拓扑结构

Fig.1 General topology structure of the EER

图2 电能路由器端口电力电子结构示意图

Fig.2 Power electronic structure of the EER ports

图3 轮盘赌选择示意图

Fig.3 Schematic diagram of roulette wheel selection

图4 种群进化过程

Fig.4 Process of population’s evolution

图5 修改后的IEEE RTS-79测试系统

Fig.5 Modified IEEE RTS-79 test system

图6 发电机出力数据

Fig.6 Output data of the generators

图7 电能路由器端口参数设置

Fig.7 Port parameter settings of EER

图8 原始系统和计及电能路由器系统的运行状态对比

Fig.8 Comparison of the operating status of the original system and the EER system

表1 不同场景下电能路由器端口参数的计算结果

Table 1 Calculation results of EER’s port parameter in different scenarios

图9 电容器组的无功补偿容量

Fig.9 Reactive power compensation capacity of capacitor banks

表2 无功优化的统计结果

Table 2 Statistical results of reactive power optimization

图10 IEEE RTS-79节点系统有功网损

Fig.10 Active power loss of IEEE RTS-79 system

图11 IEEE RTS-79节点系统电压偏离度

Fig.11 Voltage’s deviation of IEEE RTS-79 system

图12 IEEE RTS-79节点系统各节点电压

Fig.12 Node voltages of IEEE RTS-79 system

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基于改进教与学算法的含电能路由器的电力系统无功优化

Reactive Power Optimization of Power System with Electric Energy Router Applying Modified Teaching-Learning Algorithm

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