A self-organizing fuzzy inference system for electric field optimization of HV electrode systems

Development of efficient methods for optimum design of electrode and insulator contour in a HV apparatus has been an important area of research in the recent past. A self-organizing fuzzy inference system is developed for electrode optimization which is an improved version over traditional iterative approach of optimization and more recent methods employing neural networks. This fuzzy system has been implemented for two practical examples of an axisymmetric single-phase gas-insulated system (GIS) bus termination and a disconnecter switch configuration. Improved electric stress distribution demonstrates the usefulness of the proposed method. A new methodology for automatic generation of the fuzzy rule base from the input-output data set is also proposed in this scheme. This fuzzy system is much simpler and less time consuming to implement compared to other optimization techniques presently available for optimization of HV electrodes.