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Directional Overcurrent Relay (DOCR) coordination computation allowing for desired and high level accuracy in interconnected power systems is very difficult and is a highly constraint oriented optimization problem. This paper aims to study the effectiveness of a newly reported optimization technique, Teaching Learning Based Optimization (TLBO), in protective relay coordination comparing with a widely used optimization technique, Particle Swarm Optimization (PSO).

DOCR coordination in electric power systems is considered as an optimization problem by formulating objective function and specifying problem constraints. Optimum values of the DOCR adjustment parameters (Time Dial Setting and Plug Setting) in terms of reliable coordination margin and operating times of relays are computed by both the algorithms, TLBO and PSO. Optimal coordination is verified in three test bus systems: IEEE 6-bus, WSCC 9-bus and IEEE 14-bus systems.

A comparison between the numerical results of using both the algorithms indicates that the TLBO gives better results in terms of the total operating times of relays and Coordination Time Interval (CTI).

This paper represents the performance of a newly reported optimization technique, TLBO which is till now unpopular to protection engineers to be applied in protective relay coordination applications. The technique provides better performance in comparison to the widely applied technique, PSO. It is expected that TLBO would facilitate protection engineers to decide the optimum and appropriate settings of the relays for leading exact relays coordination.