Modified cataclysmic genetic Algorithm applied in optimal power flow of power system

The optimal power flow problem (OPF) is a complicated nonlinear mixed optimal problem with multi-objectives. The traditional optimization methods, such as linear and nonlinear optimization methods has obvious deficiencies of the dispersed variable approximation, and it can not achieve the reality of global optimization. This paper presents an improved algorithm for optimal power flow of power system_ modified cataclysmic genetic Algorithm (MCGA). It overcomes the traditional genetic algorithm(GA) shortcomings of long computation time and easily converging into local extreme value point, and has the optimization process is short and the advantages of global optimization. Moreover MCGA is a global optimization algorithm which is suitable for solving complex and mixed nonlinear optimization problems with dispersed variables. Through calculations of practical power system example show, that this method proposed in this paper has a stable, fast calculation, and ideal optimal results characteristics.