Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

Article retrieval

文章检索

首页 >> 文章检索 >> 最新索引

遗传算法优化BP神经网络的电能质量预测预警研究

来源:电工电气发布时间:2021-09-18 12:18 浏览次数:39

遗传算法优化BP神经网络的电能质量预测预警研究

武晨晨1,苗霁1,祝佳楠1,张文惠2
(1 国网江苏省电力有限公司宿迁供电分公司,江苏 宿迁 223800;
2 南京理工大学 自动化学院,江苏 南京 210094)
 
    摘 要:电能质量稳态指标的预测和预警对于优化电网运行方式具有重要意义。以某监测点为研究对象,根据该监测点的历史天气信息、有功功率、无功功率和电能质量数据,使用遗传算法改进 BP 神经网络,构建复合型神经网络预测系统。给出了电能质量分等级预警方式,通过模糊聚类合理灵活地设置阈值并给出电能质量预警信息,以适应不同场合的预警。算例验证证明了该方法的有效性与实用性。
    关键词:电能质量;遗传算法;BP 神经网络;预测;预警;模糊聚类
    中图分类号:TM933.4     文献标识码:A     文章编号:1007-3175(2021)09-0018-05
 
Power Quality Prediction and Warning Based on BP
Neural Network Optimized by Genetic Algorithm
 
WU Chen-chen1, MIAO Ji1, ZHU Jia-nan1, ZHANG Wen-hui2
(1 State Grid Jiangsu Electric Power Co., Ltd Suqian Power Supply Branch, Suqian 223800, China;
2 School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)
 
    Abstract: The prediction and warning of power quality steady state indices is of great significance to optimize the operation of power grid.In this paper, a certain monitoring point is taken as the research object and the data about its historical weather information, active power, reactive power and power quality are performed., The genetic algorithm is utilized to improve the BP neural network and a complex neural network prediction system is constructed accordingly. This prediction system could warn by the grades of power quality and could set threshold value reasonably and flexibly by the use of fuzzy clustering aiming at giving warning information which is available for various situations. In the end ,this method is verified effective and practical by an example.
    Key words: power quality; genetic algorithm; BP neural network; prediction; warning; fuzzy clustering
 
参考文献
[1] SONG J, XIE Z, ZHOU J, et al.Power quality indexes prediction based on cluster analysis and support vector machine[J].CIRED-Open Access Proceedings Journal,2017(1) :814-817.
[2] 李君卫, 汤亚芳, 郝正航, 等. 聚类分析及其在电力系统中的应用综述[J] . 现代电力,2019,36(3) :1-10.
[3] 林顺富,汤继开,汤波,等. 典型电能质量 z 稳态指标预测模型研究[J] . 电网技术,2018,42(2) :614-620.
[4] 赵秀平. 基于多种预测方法的电能质量预警机制研究与实现[D]. 北京:华北电力大学,2016.
[5] 刘建华,刘艳梅,冯纯纯,等. 基于 k 中心点聚类的稳态电能质量预警阈值研究[J] . 电测与仪表,2018,55(23) :41-45.
[6] ZEJUN D, PING L, SEN O, et al.Mechanism of Power Quality Forecast and Early Warning and Their Application[J].Proceedings of the CSUEPSA,2015,27(10) :87-92.
[7] 丁泽俊,刘平,欧阳森,等. 电能质量预测与预警机制及其应用[J] . 电力系统及其自动化学报,2015,27(10) :87-92.
[8] 卢珏,孙云莲,谢信霖,等. 基于改进组合预测的电能质量预警研究[J] . 电工电能新技术,2020,39(9) :65-73.
[9] 苏卫卫,马素霞,齐林海. 基于 ARIMA 和神经网络的电能质量稳态指标预测[J] . 计算机技术与发展,2014,24(3) :163-167.
[10] 王芳,顾伟,袁晓冬,等. 面向智能电网的新一代电能质量管理平台[J] . 电力自动化设备,2012,32(7) :134-139.
[11] 王同勋,杨岑玉,彭傊,等. 一种电能质量预警系统及其方法:CN103647276A[P].2014-03-19.
[12] 欧阳森,李奇,石怡理,等. 考虑模糊聚类特性的电能质量预警方法及其应用[J] . 电网技术,2014,38(6) :1712-1716.