Abstarct: Abstract By restructuring the electricity industry from a vertically integrated model to a competitive one, the importance of retailers in the electricity market has increased. Given the key role of retailers in optimizing the energy supply for end consumers, it is essential to study and analyze the factors affecting their performance and provide scientific and practical solutions to improve their profitability and manage financial risks. In this thesis, the decision-making problem of a retailer in Iran electricity market is modeled as a linear programming problem. Aiming to maximize profit from energy sales to consumers, the retailer procures energy at a lower price through long-term bilateral contracts and medium-term forward contracts in the energy exchange market. A two-stage stochastic programming approach is employed to manage the uncertainty in energy prices in various forward contracts in the energy exchange market. In the first stage, the energy purchased volume through bilateral contracts is determined at the beginning of the planning horizon. In the second stage, the energy purchased volume through forward contracts and green electricity is determined monthly throughout the planning horizon. The proposed model has been implemented to supply the energy demand of two sample factories located in Semnan Province. The results indicate that, under a risk-neutral strategy, 94.09% and 5.91% of the annual energy of 714.95 MWh are met by bilateral contracts and the energy exchange market, respectively. In contrast, adopting a risk-averse strategy decreases the supplied energy to 498.58 MWh, with 77.14% purchased from bilateral contracts and 22.86% purchased from the energy exchange market. As risk aversion increases, the retailer’s annual profit decreases by 31.4%.