基于改进遗传算法的配电网电容器优化配置

摘要：21世纪的今天，电早已维系和贯穿着人们的日常生活。随着科技的发展和社会的进步，电力需求越来越大，配电网容量不断增加，进而对电网无功要求也逐日增加。无功补偿电容器作为配电网中最主要的无功补偿设备之一，也显得越来越重要，越来越值得人们去研究。因此，合理的投运电容器组，寻求电力系统的电容器优化补偿理论和实用技术，优化无功补偿，对减小网络损耗、改善系统的电能质量、增强系统供电能力有着重要意义。本文主要针对电容器优化的研究现状，提出合理的优化模型，针对所建立的优化模型，将一种改进的遗传算法应用到配电网电容器的优化配置问题中。65425

毕业论文关键词：配电网，无功补偿，遗传算法，电容器优化配置

Abstract：In twenty-first Century, electricity has to maintain and run through the daily life of people. With the development of science and technology and social progress, the demand for electricity is growing more and more, increasing capacity distribution network and the grid no energy requirements are also increasing day by day. Reactive power compensation is more and more important, more and more worthy of study. Reactive compensation capacitor as the distribution network is the most important one of the reactive power compensation device. Therefore, the reasonable operation of capacitor group, seek power system optimal capacitor compensation theory and practical technology, optimization of reactive power compensation and to decrease network loss, improve system of electric energy quality, and enhance the capacity of power supply system is of great significance. This paper in view of the current situation of capacitor optimization research, put forward a reasonable optimization model, according to the established optimization model, an improved genetic algorithm is applied to distribution network capacitor allocation optimization problem.

Keywords: distribution network, reactive power compensation, genetic algorithm, optimal capacitor allocation

1 绪论 4

1.1 配电网电容器优化的意义 4

1.2 配网电容器优化配置的研究现状 5

1.3 本文的主要工作 6

2 配电网电容器优化配置的基本原理 6

2.1 配电网中的无功损耗和无功电源 6

2.2 无功与电压的关系 7

2.3 无功功率与功率因数的关系 7

2.4配网电容器优化配置数学模型 9

3 GA算法及解决电容器优化配置的步骤 10

3.1 遗传算法的概念 10

3.2 遗传算法的流程 12

3.3 遗传算法的优缺点 13

3.4 遗传算法的改进 14

3.5 遗传算法实现电容器优化配置的步骤 14

4 算例验证 15

结论 17

参考文献 18

致谢 19

附录 20

1 绪论

1.1 配电网电容器优化的目的与意义

在工业企业供电中，绝大部分用电设备（如感应电动机、变压器、电抗器、电焊机等）为感性负荷，这些设备不仅需要从电力系统吸收有功功率，还要吸收无功功率以产生正常工作所必须的交变磁场。然而在输送有功功率一定的情况下，无功功率增大，将带来以下许多不良的后果：基于改进遗传算法的配电网电容器优化配置:http://www.youerw.com/zidonghua/lunwen_73058.html