This paper proposes a new methodology to include financial risk management in the framework of two-stage stochastic programming for energy planning under uncertainties in demand and fuel price. A deterministic mixed integer linear programming formulation is extended to a two-stage stochastic programming model in order to take into account random parameters that have discrete and finite probabilistic distributions. This was applied to a case study focusing on planning the capacity supply to meet the projected electricity demand for the fleet of electricity generation stations owned and operated by Ontario Power Generation (OPG). The objective of the proposed mathematical model is to minimize cost subject to environmental constraints. The case study is investigated by considering only existing technologies and also by considering the integration of new technologies that help achieve stricter carbon reduction requirements. (C) 2014 Elsevier Ltd. All rights reserved.