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This paper describes optimal power flow calculation in which the fuel cost function is used as the problem objective. Key cutting algorithm (KCA) based optimal power flow is formulated and then challenged in comparison with particle swarm optimization (PSO) and genetic algorithms (GA). Two standard test functions called Schaffer functions are tested. Also, a IEEE standard 6-bus, 14-bus and 30-bus test power system are employed. The solutions obtained by the proposed method are superior and very useful. The algorithm and simulation are carried out using MATLAB programming. As a result, all search algorithms can solve the optimal power flow problems however the key cutting algorithm-based optimal power flow gives the best solutions over the other two optimal power flow methods for the average and standard deviation values of the fuel cost.