Contents I. Introduction
A well-coordinated OCPDs limit the negative effects of fault currents although the manual coordination method is a cumbersome task to perform [1], [2] & [4]. The spate of technical papers has shown that optimization techniques can be applied to reduce the time spent doing OCPD coordination study and provide the best set of OCPD settings. Such optimization techniques are simplex and dual simplex, evolutionary algorithm, interval coordination algorithm, neural networks, artificial intelligence, General Algebraic Modelling Systems (GAMS), and Convex Optimization, as mentioned in [11], [12], & [13]. All these optimization techniques provide a similar set of settings; however, the most popular method is the GA search process. Given that the optimum coordination of OCPD is considered a value advantage problem, the use of GA is regarded as a mature algorithm with a global optimization solution having a reasonable convergence rate and accuracy [14]. The use of GA in OCPD coordination, such as overcurrent relays (OCR) and directional overcurrent relays (DOCR), can be seen in numerous research. Both OCR and DOCR are actuated by overcurrent from shunt fault. The only difference is the directional element of the DOCR, wherein it only sends a trip signal to the circuit breaker if the direction of the fault current is the same as its setting. [7], [8], [15], [16] used GA in the coordination of OCRs, while [9]–[15] used GA to coordinate DOCRs. All used the IEEE bus as a test case system except for [7], [16], which includes an actual industrial plant and transmission system. Such research documentations prove the effectiveness of GA application in both academia and industry. Although popular simulation software such as SKM [17] and ETAP [18] have autocoordinate features that use artificial intelligence to process numerous data, this is an expensive add-on to the base package of the software.
