中国电力 ›› 2016, Vol. 49 ›› Issue (10): 142-147.DOI: 10.11930/j.issn.1004-9649.2016.10.142.06

• 新能源 • 上一篇    下一篇

基于小波变换的分布式发电孤岛检测方法

蒋小平,葛畅,桂萌   

  1. 中国矿业大学 机电与信息工程学院,北京 100083
  • 收稿日期:2016-05-15 出版日期:2016-10-10 发布日期:2016-11-07
  • 作者简介:蒋小平(1966—),男,北京人,硕士,副教授,从事电力系统自动化及控制工程研究工作。E-mail: 1229320654@qq.com
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(00-800015G2)

Islanding Detection of Distributed Generation based on Wavelet Transform

JIANG Xiaoping, GE Chang, GUI Meng   

  1. School of Mechanical, Electronic & Information Engineering, China University of mining & Technology, Beijing 100083, China
  • Received:2016-05-15 Online:2016-10-10 Published:2016-11-07
  • Supported by:
    This work is supported by the Fundamental Research Funds for the Central Universities (No.00-800015G2).

摘要: 为保证电力用户的供电质量和电力系统的安全运行,分布式发电系统(distributed generation,DG)要求具有孤岛检测功能。针对分布式发电系统中传统孤岛检测方法的不足,提出一种基于小波变换的孤岛检测方法。该方法用小波变换从公共连接点(point of common coupling,PCC)的电压提取小波系数,并求其标准偏差和能量值的平均值,再通过设置的门槛值来判断是否发生孤岛。研究结果表明,该方法克服了传统孤岛检测方法的缺点,同时,仿真结果验证了该方法能够快速、准确地检测到孤岛的发生,并表明即使在各种扰动下,也不会发生误动作。

关键词: 分布式发电, 孤岛检测, 小波变换, 标准偏差

Abstract: To ensure the power supply quality for power customers and the safe operation of power systems, the distributed generation system is required to have islanding detection functions. In view of the shortcomings of conventional islanding detection methods for distributed generation systems, a new islanding detection method is proposed based on the wavelet transform. This method uses the wavelet transform to extract wavelet coefficient from the voltage of point of common coupling (pcc), and calculates the mean values of standard deviation and energy value of wavelet coefficient, and then determines the islanding through the preseted threshold value. It is proved through simulation that by overcoming the shortcomings of the conventional islanding detection methods, the proposed method can detect the occurrence of islanding quickly and accurately, and misoperation cannot happen even under various disturbances.

Key words: distributed generation, islanding detection, wavelet transform, standard deviation

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