Co-optimization of Microgrid's bids in Day-ahead Energy and Reserve Markets Considering Stochastic Decisions in a Real-time Market

High penetration of distributed energy resources in distribution networks is facilitated through the microgrids (MGs) structure. From the technical point of view, the MG operator (MGO) is responsible for the internal operation of the MG regarding which the distribution system operator (DSO) cannot take any decision. From the market viewpoint, the MGO participates in the wholesale markets regarding which the scheduling of the MG's resources is monitored. Therefore, the operation problem of the MGO considering its participation in the wholesale markets under uncertainty has been investigated in many studies. In this paper, a two-stage stochastic optimization approach is developed to model the MGO's bidding strategies in the day-ahead energy and reserve markets considering its stochastic decisions in a real-time market. In this model, the uncertainties of demand, wind speed, and solar radiation are modeled through different scenarios using the probability distribution functions (PDFs) of these parameters. Moreover, the uncertainty of the real-time energy price is modeled using the information gap decision theory (IGDT) method. To show the effectiveness of the model, it is applied on a MG test system