Study on Fault Line Detection Based on Genetic Artificial Neural Network in Compensated Distribution System

摘要：

The faulty line detection of single phase to earth fault in power system with neutral grounding via arc suppression coil has not been well solved. The commonly used single faulty line detection methods, such as wavelet transform method, the fifth harmonic current method and zero sequence current active components method, etc., can only process partial fault information, so their reliability of faulty line detection is not satisfied. Here, by means of constructing both relative fault measurement function and confirmable fault measurement function the fault measurement function of each faulty line detection method is determined, then using genetic neural network the intelligent fusion of practical fault measurements of those faulty line detection methods is conducted, thereby the faulty line detection result with higher reliability can be obtained. Simulation results by EMTP show that the faulty line detection result by the proposed method is more precise and possesses stronger robustness.

关键词： Genetic neural network fault line detection compensated distribution network.

作者: Tao Ji Qingle Pang Xinyun Liu

作者单位: School of Information and Control Engineering, Weifang University 261061 Weifang, China School of Control Science and Engineering, Shandong University 250061 Jinan, China;School of Physics School of Physics Science and Information Technology, Liaocheng University 252059 Liaocheng, China

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 1427-1431

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）