Abstract-
I. INTRODUCTIONThe primary protection in distribution and sub-transmission networks and backup protection in transmission networks are usually provided using DOCRs [1]. For reducing the chances of excessive power outages, only faulted section of the power system is isolated using primary relays as quickly as possible. As long as the primary relay fails to operate, the backup relays have to instigate to clear the fault after the prescribed time interval. This practice is called relay coordination. The proper coordination of primary and backup relays is essential to ensure the reliability of protection scheme, which is achieved by locating the optimal values of PS and TMS. In modern multi-loop and multi-source interconnected power systems, finding the optimal PS and TMS using analytical methods becomes very hard. Alternatively, it can be easily solved by optimization techniques [2].In the last few years, several optimization techniques are employed to solve the relay coordination problem. Among the conventional methods, Linear Programming (LP) technique gained good recognition to solve this problem, including simplex, two-phase simplex and dual simplex methods [3][4][5]. The LP methods involve assumptions in PS, allowing for operating time of each relay as a linear function of TMS. In [6,7], Sequential Quadratic Programming (SQP) has been used in order to optimize both TMS and PS. Afterwards, Artificial Intelligence (AI) techniques are studied more to solve the coordination problem such as GA The HSA is one of the metaheuristic optimization methods which is developed by Z.W. Geem [22]. It has the characteristics of fast convergence speed, easy in concept and simple in implementation with only a few parameters and mathematical requirements [22,23]. Same as other metaheuristic methods, the performance of the HSA experiences a serious problem of sensitive parameters setting. Hence, fine tuning of the parameters are required, which can help the HSA to maintain a balance between diversification and intensification and to explore the population in the evolution process [24]. To improve the performance of HSA, IHSA is presented in