Virtual power plant (VPP) can be studied to investigate how energy is purchased or sold in the presence of
electricity market price uncertainty. The VPP uses different intermittent distributed sources such as wind turbine,
flexible loads, and locational marginal prices (LMPs) in order to obtain profit. VPP should propose bidding/offering
curves to buy/sell from/to day-ahead market. In this paper, robust optimization approach is proposed to achieve the
optimal offering and bidding curves which should be submitted to the day-ahead market. This paper uses mixed-integer
linear programming (MILP) model under GAMS software based on robust optimization approach to make appropriate
decision on uncertainty to get profit which is resistance versus price uncertainty. The offering and bidding curves of
VPP are obtained based on derived data from results. The proposed method, due to less computing, is also easy to trace
the problem for the VPP operator. Finally, the price curves are obtained in terms of power for each hour, which
operator uses the benefits of increasing or decreasing market prices for its plans. Also, results of comparing
deterministic and RO cases are presented. Results demonstrate that profit amount in maximum robustness case is
reduced 25.91 % and VPP is resisted against day-ahead market price uncertainty.