Investigations on the impacts of uncertain wind power dispersion on power system stability and enhancement through PSO technique

This paper proposes the method for investigating the impacts of the uncertain grid connected wind generation on power system stability and enhancement of stability through particle swarm optimization technique. The proposed method is analytical to the parental Monte Carlo simulation. This method calculated the density function which is probabilistic in nature for computing Eigen values of large-scale power system from the density function of multiple grid connected wind power generation which is also a probabilistic one. In this paper, an example of 10-machine power system with two to three grid connected wind farms is used to demonstrate for applying this method. The stability analysis results which are a probabilistic one is verified and confirmed by the Monte Carlo simulation. It is given away that the uncertain variation of grid-connected wind generation will lead to lose the stability of the system even when it is stable. This brings out that when the level of uncertainty increases, the stability of power system worsens. In addition, this paper focuses onto the instability by relating it to some general stabilizing devices like Automatic Voltage Regulator (AVR) and Power System Stabilizer (PSS). From the study, it can be inferred that these things can reduce the instability for large-scale integration of wind generation. The stability level has been enhanced through various level of optimization using PSO technique.