We compare approaches for addressing uncertainty in the joint scheduling of a combined power and gas system, with the goal of minimizing the total cost of meeting demands for gas and electricity, while satisfying operational and equilibrium constraints. A stochastic programming model and a deterministic model with reserves are formulated to investigate the hourly unit commitment and economic dispatch in the power system as well as the hourly working schedule of the natural gas system. The deterministic model uses reserves proportional to the wind energy forecast to mitigate the effect of the uncertainty in wind energy, whereas the stochastic programming model makes the day-ahead decisions while explicitly considering the wind energy uncertainty. Nonlinear constraints on the gas flows in pipelines are linearized with binary variables where, based on numerical experimentation, the number of piecewise linear segments is chosen to balance accuracy and computational efficiency. A six-bus power system with seven-node gas system and the IEEE 24-bus power system with adjusted Belgian 20-node gas system are analyzed. The simulation results indicate that, when the total wind capacity exceeds 15% of the conventional generation capacity, the stochastic programming model produces schedules with comparable or lower cost and energy shortages than the deterministic model with reserves.