Fault Identification and Classification in Transmission Line by ANN Technique Using Levenberg-Marquardt Algorithms
| Author(s) | : | Dr. Rajveer Singh |
| Institution | : | Department of Electrical Engineering, Jamia Millia Islamia, New Delhi-110025 |
| Published In | : | Vol. 4, Issue 11 — November 2017 |
| Page No. | : | 951-958 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
It is very important to identify and classify the nature of transmission line fault for reliable power flowand efficient operation of power system. It is also important for relaying decision and auto reclosing requirements. Theintroduction of pattern recognizer has provided great progress in the power system protection. Artificial Intelligence (AI)such as artificial neural network (ANN) can be utilized for recognition and classification of fault in transmission line.The ANN method requires three phase voltage and current at fault point. These signals are applied at input of the ANNpattern recognizer. Training, validation and testing are the three essential steps employed in ANN. The back propagationlearning technique is used along with Levenberg-Marquardt algorithms.
Dr. Rajveer Singh, “Fault Identification and Classification in Transmission Line by ANN Technique Using Levenberg-Marquardt Algorithms”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 11, pp. 951-958, November 2017.
