Optimal coordination of directional over-current relays using Teaching Learning-Based Optimization (TLBO) algorithm

Abstract

Relay Coordination in a big distribution system with multiple meshes and bidirectional power feed becomes very Complex for protection engineers. Manual and graph theory based approaches were applied successfully in small power system. In a big distribution system linear and non-linear programming based optimizing techniques are applied for relay coordination. Presently, artificial intelligence techniques are applied for optimal co-ordination of directional overcurrent relays. This paper discusses the application of Teaching Learning Based Optimization (TLBO) algorithm for optimal coordination of DOCR relays in a looped power system. Combination of primary and backup relay is chosen by using Far vector of LINKNET structure, to avoid mis-coordination of relays. Coordination of DOCR is tested for IEEE 3, 4 and 6 bus systems using the TLBO. Also, the objective function is modified to optimize the operating time between backup and primary relays. The results are compared with the optimized values of Time dial setting and Plug setting values obtained from modified differential evolution algorithm. The proposed algorithm TLBO gives optimal coordination margin between 0.3 and 0.8s and no miscoordination between primary and backup pairs. Results are also verified using Digsilient power factory simulation software.