Abstract: Along with large scale grid-connection of such new energy as wind power and photovoltaic (abbr. PV) power, strong correlation appears among new energy sources that are not far apart geographically apart. During the planning of existing power grid, usually the verifying calculation of the being proceeded power grid planning is conducted by the adding together the installed capacity of all wind farms and PV stations, however, due to the mutually complementary between wind power and PV power, there is very few probability by which the wind power and PV power simultaneously reach their maximum power output, so such a verifying calculation may lead to the waste of power grid resources and makes the economy decreased. For this reason, a probabilistic power flow analysis model considering the group output characteristic was proposed, and a method combining cumulant and Gram-Charlier series expansion was put forward to solve this model. Taking IEEE 10-macbine 39-bus system connected with wind power and PV power as the reference system, the obtained results were compared with that by Monte Carlo simulation to verify the effectiveness and accuracy of applying the proposed model and algorithm to probabilistic power flow. By means of analysis, the obtained conclusion shows that without considering the wind-PV correlation the power flow in tie-line is always larger than that with wind-PV correlation considered.