“…Numerous factors such as membership function, fuzzy rules, transfer function model, number of input and output layers and method of training the network can affect the output of the designed controller. Additionally, implementation of such controller in real-time for ALFC application is a cumbersome process and requires field expertise [8], [10], [11]. Therefore, the gain parameters of classical controllers are obtained using population-based evolutionary computational intelligence approaches such as GA [10], PSO [12], QOHSA [13], GOA [14], HHO [15], HBFO [16], HIF-PS [17], BA [18],QSHO [19]and other numerous approaches for controlling the ACE of interconnected multiarea multi-source power system.…”