A virtual power plant (VPP) consisting of a wind farm

a pumped storage power plant and three gas turbines is considered. Able to participate in the operation of the mid-term contract market

the day-ahead market and the balancing market

VPP has maximum profits as its optimization objective. Owing to the uncertainty of electricity price

wind power output and power unbalance penalty

the bidding of VPP faces risks. As the electricity price can be accurately predicted and the error distribution characteristics can be precisely described

a stochastic programming approach is used to deal with price uncertainty. In view of the low prediction accuracy of wind power output and the inability of accurate characterization of probability distribution

a robust optimization approach is used to deal with the uncertainty of wind power output. The uncertain wind power output is confined to a certain interval

and optimal scheduling schemes for suppressing the impact of uncertainty in different degrees are obtained by adjusting the robust coefficient. Based on the two approaches

a robust stochastic bidding model of VPP considering environmental cost is developed. By applying the proposed model

the actual profit of VPP can be improved while computational burden is reduced. Numerical results show that this model is effective.