<p>Hybrid power systems are the way forward at present. Considering the environmental pollution aspect associated with conventional energy systems, hybrid power systems undoubtedly offer a much greener and cleaner energy production. At the same time the efficiency of both the conventional and the hybrid energy power systems are a matter of consideration regarding the acceptability of the same. In this respect quick and precise identification of the location of faults is very essential to increase the efficiency of the proposed energy system. Considering the optimization algorithms such as artificial humming bird algorithm, chaotic artificial humming bird algorithm, oppositional artificial humming bird algorithm used in some research works, the present study focuses on another optimization algorithm known as quasi oppositional based chaotic artificial humming bird algorithm (QOCAHA) in terms of its more quicker and accurate detection of fault locations in the transmission line. The paper considers a maximum transmission line length of 300&#xa0;km along with least magnitude of absolute of percentage error for the fault location being reported as 0.0001 for the conventional system (Phase C to Ground fault) and 0.0001 reported for the hybrid system involving conventional and solar combination (Phase C to Ground fault) which happens to be the best finding as reported by QOCAHA.</p>