Abstract：In order to cope with the impact of large-scale access to new energy sources such as wind power，

photovoltaic and electric vehicles on the spatial characteristics of the power grid，a novel dynamic probabilistic

trend analysis method was proposed. Firstly，the probability distribution model of wind and light power was

established by combining parametric and nonparametric probabilistic modelling theories，and the Copula function

was constructed to portray the wind and light power correlation. Secondly，the electric vehicle（EV）charging load

model was established by taking the constraints of the road network and the influence of external factors into

consideration. Finally，the Nataf transform and singular value were combined to generate the wind and light power

samples with correlation，and the simulation analysis of the case39 case system taking into account the correlation

of wind and solar power outputs and EV charging loads was carried out by combining the cumulant method and

Gram-Charlier series expansion methods，and the results show that the probability distribution of the bus voltage of

photovoltaic power generation in the 10：00—15：00 grid shows a decentralized trend，and the probability

distribution of the bus voltage decreases by 30.37% after being connected to the grid，and the probability distribution of the bus voltage of wind power generation in the 11：00—18：00 bus voltage shows a centralization trend，and the bus voltage probability distribution rises by 80.7% after grid connection，while large-scale electric vehicle charging loads are put into the grid will affect the operation characteristics of the system，which makes the bus voltage expectation value decrease by an average trend of 1.36%.

      Key words：wind power；photovoltaic；correlation；dynamic probability load flow；Copula function；electric

vehicle（EV）charging load；cumulant method