Robust based optimal operation model of virtual power plant in electricity market

With the development of the electricity market, the operation strategy of virtual power plant(VPP) in the electricity market gets extensive attentions. The existing studies mainly focus on the enhancement of VPP revenue by providing energy to the electricity market. Due to the uncertainty of renewable energy sources in VPP, stochastic optimal scheduling model is usually used to generate the optimal operation strategy. However, the accurate probability distribution functions of uncertainty parameters in stochastic optimization method is difficult to obtain, meanwhile, the stochastic optimization method needs to generate a large number of scenarios, which has heavy computation burden for optimizing the operation strategy . In this paper, a robust optimization model is proposed to optimize the operation strategy of VPP in the electricity market. In order to increase the revenue of VPP and decrease the gap between the output of VPP in real-time market and the bidding capacity in the day-ahead market, an optimal scheduling model is established considering demand response. Furthermore, the model is transformed into a mixed integer linear programming(MILP) model using duality theory, which can be solved efficiently by CPLEX. The solution of the robust model can guarantee the reliability and feasibility in the predefined uncertainty sets of the resources of the VPP. Finally, numerical results demonstrate the efficiency and applicability of the proposed model.