An Online Intelligent Alarm-Processing System for Digital Substations

A flood of alarm messages in an automatic digital substation makes the monitoring task a significant challenge for the operators in a remote control center, especially under fault scenarios. An online intelligent alarm-processing system is developed based on the architecture of the digital substation. First, real-time alarms are classified according to the IEC 61850 standard in order to provide synthesized and organized alarms for the alarm-processing procedure in the next step. Then, a new and systematic alarm-processing approach for digital substations is developed. Two modules (i.e., the generation of candidate hypotheses and the truth evaluation for the hypotheses) are included in the developed approach, and these two modules are operating in parallel in online implementation. This approach could not only determine the fault/disturbance cause but also the missing or false alarms as well as the causes of the false alarms. According to actual application requirements, an online intelligent alarm-processing system is developed and applied in the Xingguo substation-the first digital substation in Jiangxi Province, China. Finally, an actual alarm-processing scenario serves to demonstrate the presented alarm-processing method as well as the developed software system.

[1]  Y. C. Huang.  Fault Section Estimation in Power Systems Using a Novel Decision Support System , 2002, IEEE Power Engineering Review.

[2]  M. Kezunovic,et al.  Implementing Fuzzy Reasoning Petri-Nets for Fault Section Estimation , 2008, IEEE Transactions on Power Delivery.

[3]  Young-Moon Park,et al.  A fault diagnosis expert system for distribution substations , 2000 .

[4]  Jarmo Partanen,et al.  Using fuzzy sets to model the uncertainty in the fault location process of distribution networks , 1994 .

[5]  A. P. Alves da Silva,et al.  Neural networks for fault location in substations , 1996 .

[6]  Jianbo Xin,et al.  An Analytic Model-Based Approach for Power System Alarm Processing Employing Temporal Constraint Network , 2010, IEEE Transactions on Power Delivery.

[7]  J. Trecat,et al.  Power systems fault diagnosis using Petri nets , 1997 .

[8]  Chen-Ching Liu,et al.  A new logic-based alarm analyzer for on-line operational environment , 1996 .

[9]  P.A. Crossley,et al.  Unsupervised event extraction within substations using rough classification , 2006, IEEE Transactions on Power Delivery.

[10]  R.E. Mackiewicz,et al.  Overview of IEC 61850 and Benefits , 2006, 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition.

[11]  J. Trecat,et al.  Extended Petri net models for fault diagnosis for substation automation , 1999 .

[12]  Wen-Hui Chen,et al.  On-line fault diagnosis of distribution substations using hybrid cause-effect network and fuzzy rule-based method , 2000 .

[13]  Fushuan Wen,et al.  Tabu search approach to alarm processing in power systems , 1997 .

[14]  H.H. Zurn,et al.  Application of neural-network modules to electric power system fault section estimation , 2004, IEEE Transactions on Power Delivery.

[15]  F. Wen,et al.  NEW APPROACH TO ALARM PROCESSING IN POWER SYSTEMS BASED ON THE SET COVERING THEORY AND A REFINED GENETIC ALGORITHM , 1998 .

[16]  Chen-Ching Liu,et al.  Multiple hypotheses and their credibility in on-line fault diagnosis , 2001 .

[17]  Dipti Srinivasan,et al.  Automated fault detection in power distribution networks using a hybrid fuzzy–genetic algorithm approach , 2000 .

[18]  Gerasimos Rigatos,et al.  Neural network-based approach for early detection of cascading events in electric power systems , 2009 .

[19]  P.A. Crossley,et al.  Building Knowledge for Substation-Based Decision Support Using Rough Sets , 2007, IEEE Transactions on Power Delivery.

[20]  Hong-Tzer Yang,et al.  Abductive network model-based diagnosis system for power transformer incipient fault detection , 2002 .

[21]  Kwang-Ho Kim,et al.  Adaptive fault section estimation using matrix representation with fuzzy relations , 2004 .

[22]  Yong-Hua Song,et al.  Fault diagnosis of electric power systems based on fuzzy Petri nets , 2004 .

[23]  T.S. Sidhu,et al.  Control and automation of power system substation using IEC61850 communication , 2005, Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005..

[24]  H.H. Zurn,et al.  Identifying the Primary Fault Section After Contingencies in Bulk Power Systems , 2008, IEEE Transactions on Power Delivery.