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Optimal Power Flow algorithm is important for the load flow solution in open market for operating the electrical network in optimal way. The optimal power flow in which certain controllable variables is adjusted to minimize the certain objective function while satisfying the constraints on the system operating limits. The global solution is obtained quickly using conventional and evolutionary methods. Evolutionary methods like Genetic Algorithm finds its utility in optimal power flow solutions .Though the G.A.is simple to apply but the global solution is not considered due to slow rate of convergence. This paper presents a comparative study of conventional OPF algorithms and GA based four proposed algorithms. The proposed algorithms suggests a new set of control and state variables which speed the convergence rate with improved optimal solution. The proposed algorithms tested on IEEE-30 bus system and the results were presented in this paper.

Effect of Selection of Control and State Variables on Convergence of GAOPF