The power system engineers dire need of extraordinary methods to optimally analyze, monitor and control various elements of such an advanced complicated system that include economic load dispatch, unit commitment, automatic generation control, state estimation and Optimal Power Flow (OPF). It is a static nonlinear problem that optimizes a specific objective function while satisfying a set of physical and operational constraints imposed by equipment restrictions and security requirements. Power system optimization problems are complex and have non-linear characteristics. There are two ways namely conventional and evolutionary methods. The conventional methods require function to be convex and variables as continuous. However, the power system optimization problems do not have these characteristics. Evolutionary optimization methods have become an alternative to conventional optimization techniques for solving real-world problems having non-convexity, non-differentiability and discontinuity. Though the evolutionary methods find suitable solutions to power system problems, premature convergence and stagnation do not use them directly.
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