An enhanced human conception optimizer for over-current relay coordination problem in distribution system

In this paper, an enhanced human conception optimizer (EHCO) is proposed to solve the over-current relay coordination problem in a power distribution system. Generally, a randomly generated population is used in most of the available metaheuristic optimizers, where some of the initial search agents may be oriented along the boundary of the search space or in the opposite direction of a possible global solution in the search space. Such a random population will lead to slow convergence. To solve such an issue, in EHCO, a healthy initial population is proposed. To avoid local trapping problems, a wavelet mutation concept is also proposed. The convergence performance of the EHCO is tested with 29 benchmark functions and compared with some existing results. Two relay coordination problems with IEEE-8 bus 14 over-current relay and 7 over-current relay-based distribution systems are verified to validate the proposed optimizer for relay coordination problems. The simulation results show a 60–70% improvement in operating time for such distribution systems in comparison with existing results.