Research on Evaluation Method of Relay Protection Action Based on Fault Information

Abstract:

Research on power system fault diagnosis and method of relay protection action require the complete primary equipment topological structure of the grid. This article propose an evaluation method based on power network topology structure, which is easily implemented and it can assess the performance of breakers and protections in an entire power system. Considering the missing or error information, a protection motion capability analysis method based on genetic algorithm is proposed on the basis on that method. The simulation results on IEEE three-machine nine-bus system show that the algorithm is capable of discriminating the fault fast and accurately, and has excellent fault-tolerance capability.Keywords: Relay Protection; evaluation of action; Genetic Algorithm; fault-tolerance capability

• Periodical: Advanced Materials Research (Volumes 1044-1045)
• Pages: 490-494
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1044-1045.490
• Online since: October 2014
• Authors: Zi Nan Liu, Shi Wu Xiao, Shan Jiang
• Keywords: Evaluation of Action, Fault-Tolerance Capability, Genetic Algorithm (GA), Relay Protection

References

[1] CHEN Xiaolin, LUO Yi, et al. Protection Characteristic Analysis Method Based on Recorded Fault Data and its Implementation, Power System Technology, 2005, 29(11): 70-74.

[2] GAO Chuang, Research on Fault Diagnosis of Transmission Network and Action Performance Analysis of Relay Protections System, Tientsin University, (2010).

[3] WANG Le, Study on microcomputer relay protection of power system, Technological Development of Enterprise, 2010, 29(9): 28-29.

[4] HE Shien, LI Chengxue, et, al. Analysis on Protective Relay Mal-Operation and Suggestions for Improving Operation Reliability, Electrical Equipment, 2006, 7(4): 34-37.

[5] SUN Xiaoping, CAO Liming, Genetic Algorithm, XI'AN Jiaotong University Press, XI'AN, (1979).

[6] PAN Chong, CHEN Weigen, YUN Yuxin , et al . Fault diagnosis of power transformers based on genetic algorithm evolving wavelet neural network. Automation of Electric Power Systems , 2007, 31 (13): 88-92.

DOI: 10.1049/iet-epa:20070302

[7] XIONG Hao, SUN Caixin, CHEN Weigen, et al. Artificial immune network classification algorithm for fault diagnosis of power transformers. Automation of Electric Power Systems, 2006, 30 (6): 57-60.

[8] DU Hongwei, SUN Yaming, LIU Hongjing, et al. Fault selection diagnosis and isolation of distribution networks based on genetic algorithm. Power System Technology, 2000, 24 (5) 52-55.