Dynamic Probability Power Flow Considering Scenery Correlation Based on Copula Function

With the large-scale connection of new energy sources such as wind power and photovoltaic (PV) to the power grid, strong correlation is presented between geographically close wind farms or between PV power plants. For this reason, we propose a dynamic probability power flow calculation method considering scenery correlation. Combining parametric and nonparametric probabilistic modelling theories, we establish the probability distribution model of input random variables and construct Copula function to portray the correlation between multidimensional random input variables, so as to obtain sample data more in line with the actual operation of the system. The combination of cumulant method and Gram-Charlier series expansion is introduced to compute the dynamic flow and tested on the 39-bus system with case. The accuracy and validity of the static performance of the proposed method is verified by comparing it with the Monte Carlo method and the traditional cumulative method, which take correlation into account. Finally, the effect of scenery correlation on the dynamic flow is analyzed by means of dynamic probability density comparison plots.