Abstract— This work presents two meta-heuristic optimization approaches, namely the Whale Optimization Algorithm (WOA) and the Sine-Cosine Algorithm (SCA), which are applied to solve the AC Optimal Power Flow (ACOPF) problem in the power system. The objective is to minimize the total fuel cost of power generation while satisfying power balance equations and operational constraints of generators and transmission networks. The proposed methods are evaluated on the standard IEEE 30-bus test system.  The major benefit of the ACOPF is to find the optimal operating conditions of generators in a power system, subject to the generators` and system constraints across diverse scenarios. The performance of WOA and SCA is compared with that of a conventional Genetic Algorithm (GA) used as a benchmark. Simulation results demonstrate that the proposed algorithms achieve fuel cost values within the commonly reported range for the IEEE 30-bus AC-OPF problem, with WOA yielding a minimum fuel cost of 801.85 $/h and transmission losses of 9.36 MW. The obtained generator dispatch patterns and power loss values are consistent with those reported in recent literature. The results confirm that WOA and SCA provide competitive and reliable solutions for the AC-OPF problem while preserving the standard problem formulation.