Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems

被引：19
|
作者：
Lima, Fernando P. A. [1 ]
Lotufo, Anna Diva P. [1 ]
Minussi, Carlos Roberto [1 ]
机构：
[1] Univ Estadual Paulista, Fac Engn Ilha Solteira, Dept Elect Engn, UNESP, BR-15385000 Ilha Solteira, SP, Brazil
来源：
IET GENERATION TRANSMISSION & DISTRIBUTION | 2015年 / 9卷 / 11期
基金：
巴西圣保罗研究基金会; 瑞典研究理事会;
关键词：
CLASSIFICATION; METHODOLOGY;
D O I：
10.1049/iet-gtd.2014.1102
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This study presents a new approach to detecting and classifying voltage disturbances in electrical distribution systems based on wavelet transform and artificial immune algorithm. This proposal unifies the negative selection artificial immune algorithm with the discrete wavelet transform concept. Thus, the measurements obtained in a distribution substation by the supervisory control and data acquisition acquisition system are transformed into the wavelet domain. Afterward, a negative selection artificial immune system realises the diagnosis, identifying and classifying the abnormalities. The principal application of this tool is to aid the system operation during faults as well as to supervise the protection system. To evaluate the performance of the proposed method, two distribution systems were modelled in EMTP software: an 84-bus test system and a 134-bus real system. The results show a good performance, emphasising the precision of the diagnosis.
引用
收藏
页码：1104 / 1111
页数：8
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