Abstarct: In the literature related to decision-making by virtual power plant in futures market, operating conditions of day-ahead energy market are generally anticipated. However, the impact of day-ahead reserve and real-time reserve-energy markets on decision-making in the futures market has been ignored. In this thesis, the decision-making problem of a virtual power plant in the futures market is modeled as a mixed integer linear programming, taking into account the operating conditions in the energy and reserve markets. The virtual power plant includes conventional and wind power plants, energy storage unit and flexible demands. It faces uncertainties in available power production by generation assets and market prices when participating in the futures market. In order to tackle the uncertainties, a two-stage stochastic programming approach is used. This problem is studied baxsed on the data collected from the Spain electricity market. The results show that the expected profit decreases from risk-taking to risk-averse by 8.66%, while the conditional value-at-risk metric increases by 0.55%. Additionally, the effect of risk strategy on the profitability metrics is reduced by incorporating day-ahead reserve and real-time reserve-energy markets into decision-making process in the futures market.