The liberalization of the European energy market has enabled big gas customers and public utilities to build a portfolio of different gas supplies and purchase contracts. The covering of the gas demand, which is heavily temperature dependent, can be optimized by combining baseload contracts, open gas delivery contracts, and the use of the capacity of underground and local pipe storage facilities. We present a two-stage stochastic linear programming model for the optimization of the gas-purchase portfolio under uncertain demand conditions while considering the cost of purchase, underground storage capacities and transportation. Furthermore, we enhance the model to explicitly consider conditional value-at-risk. We evaluate our approach based on a real-world case study. The results show that our model is computationally tractable by a standard interior point solver for hundreds of scenarios. It clearly outperforms alternative deterministic planning approaches such as scenario analysis both in terms of expected profit and robustness.