Research on probabilistic load flow method based on point estimation and dimension reduction by dominated variables

There are many uncertain factors such as the random fluctuations of load, equipment failure out of operation and the outage of distributed generation changes with the climate in power system operation, probabilistic load Flow method gets more attention. Meanwhile, with the system scale increase, the computational efficiency limits the application of probabilistic load flow (PLF). Therefore, in this paper, a dominated variables based point estimation method is proposed. A dimension reduction method is also depicted. And the point estimation samples are transformed into arbitrary correlated distribution by polynomial normal transformation and singular value decomposition. Then the calculation of PLF is transformed into several deterministic power flow calculation. Simulation on IEEE 118 bus system demonstrates the validity of the proposed method. The results show that proposed method can enhance the computational efficiency of point estimation evidently. And the utilization of singular value decomposition can easily handle the non-negative definite correlation matrix.