This paper proposes a chance constrained formulation to tackle the uncertainties of the load and wind turbine generator in transmission network expansion planning. The Monte Carlo simulation and analytical probabilistic power flow analysis are combined by simulating the probability density function of wind farm output and applying it in analytical probabilistic load flow calculation. A chance constrained transmission network expansion planning formulation considering the uncertainties of both the load and wind turbine generator is worked out. The optimization problem is solved with a two-step genetic algorithm. The formulation proposed is more computationally efficient and can deal with uncertainties in transmission network expansion planning， the efficiency shown through a test example.