INCOMING AND OUTGOING CT READINGS BASED AI TECHNIQUES FOR BUS BAR DIFFERENTIAL PROTECTION FAULTS ANALYSIS | ||
| JES. Journal of Engineering Sciences | ||
| Article 15, Volume 41, No 4, July and August 2013, Pages 1595-1611 PDF (403.94 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.21608/jesaun.2013.114885 | ||
| Authors | ||
| M. Mahmoud Ismail* 1; M. A. Moustafa Hassan2 | ||
| 1Electrical Power and Machine Department, Faculty of Engineering Helwan University | ||
| 2Electrical Power and Machine Depart. Faculty of Engineering Helwan University | ||
| Abstract | ||
| The application of artificial intelligent approaches was introduced recently in protection of distribution networks. In this paper, the application of Adaptive Neuron Fuzzy Inference System (ANFIS) as well as artificial Neural Network (ANN) for protection of bus bars will be illustrated. The objective of this paper is firstly, to detect the fault occurrence on bus bar, secondly location of the fault. The fault detection and location are firstly trained using ANN and ANFIS techniques and then they are tested in diversity of system conditions with respect to the fault types, inception instant, resistance and pre fault conditions. The fault detection and location units used current magnitude difference change at fault and Pre-fault conditions for incoming and outgoing CTs. The fault location unit in this paper is to detect if the fault occurs internally on the bus bar or externally. The protection system selection depends on the time as the system should take the correct action at fault condition, sending correct tripping signal for internal fault conditions and prevent the mal-operation due to external fault conditions. On other hand, the fault clearing time is very important issue to avoid more damage to power system equipments. From the simulation, it is found that the proposed system success to detect the fault and clarify the fault location at different fault cases within a short detection time than obtained in the previous work. | ||
| Keywords | ||
| busbar prptection; AI techniques; current transformers | ||
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