AN INTEGRATED ALGORITHM FOR DETECTING AND CLASSIFYING THE FAULTS IN POWER SYSTEMS
V. Gomathy S. Sheeba Rani K. Sujatha R. Sitharthan
The power transformer is one of the important components in electric power systems and the continuity of the transformer operation is vital for maintaining the reliability of power system. In order to detect the transformer faults efficiently, some necessities such as high speed, highly sensitive and reliable protective relays are required. For this purpose, different fault detection techniques are proposed in existing works. But, it has some drawbacks such as magnetizing inrush current which always exists during energization of power transformers. In order to overcome these drawbacks, a new fault detection technique, namely, Improved Particle Swarm Optimization (IPSO) – Support Vector Machine (SVM) technique is proposed. It efficiently detects the faults in a transformer by using a Dissolved Gas Analysis (DGA). In order to improve the performance of fault detection and classification, an integration of Evolutionary Particle Swarm Optimization (EPSO), Cuckoo Search Optimization (CSO), Relevance Vector Machine (RVM) and fuzzy logic system are proposed.
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