A chance constrained programming model is built to the stochastic optimal power flow problem（S-OPF） considering load probabilistic distributions. Based on the interior point method for deterministic optimal power flow（D-OPF） and probabilistic load flow method， a heuristic solution approach is proposed to solve the model. This approach makes use of the results of D-OPF and checks if the chance constraints are satisfied through obtaining distributions of the chance constrained variables. If a chance constraint is violated， new upper and lower bounds to the corresponding variable are formed based on the distribution and equivalent chance constraint of the variable. Then a new D-OPF with loads equal to their expect values is solved. The iteration terminates till all the chance constraints are satisfied. Tests on a 5-bus system and the IEEE 118-bus system show the effectiveness of the proposed method.