PQ monitoring system for real-time detection and classification of disturbances in a single-phase power system

被引:90
作者
Radil, Tomas [1 ]
Ramos, Pedro M. [1 ,2 ]
Janeiro, Fernando M. [1 ,3 ]
Serra, A. Cruz [1 ,2 ]
机构
[1] Inst Telecomun, P-1049001 Lisbon, Portugal
[2] Univ Tecn Lisboa, Inst Super Tecn, Dept Elect & Comp Engn, P-1049001 Lisbon, Portugal
[3] Univ Evora, P-7000671 Evora, Portugal
关键词
digital filters; disturbance detection; morphological operation; power quality (PQ) assessment; power system monitoring; power system transients;
D O I
10.1109/TIM.2008.925345
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 paper presents a system for detection and classification of power quality (PQ) voltage disturbances. The proposed system applies the following methods to detect and classify PQ disturbances: Digital filtering and mathematical morphology are used to detect and classify transients and waveform distortions, whereas for short- and long-duration disturbances (such as sags, swells, and interruptions), the analysis of the root-mean-square (RMS) value of the voltage is employed. The proposed combined approach identifies the type of disturbance and its parameters such as time localization, duration, and magnitude. The proposed system is suitable for real-time monitoring of the power system and implementation on a digital signal processor (DSP).
引用
收藏
页码:1725 / 1733
页数:9
相关论文
共 22 条
[1]  
[Anonymous], 1995, 11592009 IEEE
[2]  
[Anonymous], VOLTAGE TRANSDUCER L
[3]  
[Anonymous], 2003, Electromagnetic compatibility (EMC)-part 4-21: Testing and measurement techniques-reverberation chamber test methods
[4]  
Bollen MAJ., 2006, SIGNAL PROCESSING PO
[5]  
CHEN Z, 2001, P PORT POWERTECH SEP, V1, P6
[6]   POWER-LINE IMPEDANCE AND THE ORIGIN OF THE LOW-FREQUENCY OSCILLATORY TRANSIENTS [J].
FORTI, MM ;
MILLANTA, LM .
IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, 1990, 32 (02) :87-97
[7]   Wavelet-based neural network for power disturbance recognition and classification [J].
Gaing, ZL .
IEEE TRANSACTIONS ON POWER DELIVERY, 2004, 19 (04) :1560-1568
[8]   Pattern recognition applications for power system disturbance classification [J].
Gaouda, AM ;
Kanoun, SH ;
Salama, MMA ;
Chikhani, AY .
IEEE TRANSACTIONS ON POWER DELIVERY, 2002, 17 (03) :677-683
[9]   COMPUTING 2-D MIN, MEDIAN, AND MAX FILTERS [J].
GIL, J ;
WERMAN, M .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1993, 15 (05) :504-507
[10]   A self-organizing learning array system for power quality classification based on wavelet transform [J].
He, HB ;
Starzyk, JA .
IEEE TRANSACTIONS ON POWER DELIVERY, 2006, 21 (01) :286-295