A probabilistic load flow method based on modified Nataf transformation and quasi Monte Carlo simulation

To expose operational risk of large-scale wind power integration system, probability distribution functions (PDFs) of input variables are required to model accurately in probabilistic load flow (PLF) analysis. Unfortunately, PDFs are difficult to obtain in reality. Therefore, a PLF method based on modified Nataf transformation and quasi Monte Carlo simulation is proposed in this paper. This method is able to establish PDF of input variables by their first several orders of moments with the employment of spline reconstruction, then quasi Monte Carlo simulation based on Sobol sequence is adopted to obtain the probability distribution of the output variables. Simulation on IEEE 30 bus system and a real power system demonstrate the validity of the proposed method. The results suggest that the proposed method not only has the advantages of modelling input variables accurately and fast convergence, but also can deal with correlation with convenience.