Abstract
The distributed energy sources (DESs) based microgrid (MG) systems are growing worldwide as they integrate these sources reliably and efficiently. As the concept of the electricity market is picking up, these highly intermittent solar photovoltaic (PV) and wind turbine (WT) power plants are being connected to the grid in the form of MG which has the option of storage as well. The PV and WT power generations may vary from the forecasted generations, which leads to unreliable bidding offers in the electricity market through the bidding process. Further, leads to revenue loss due to penalties imposed for violating the agreements. They can participate in the electricity markets reliably if the MG has a properly sized storage system, which takes care of the deviations in generation for optimal, efficient, and reliable bidding. In this paper, a mathematical model for an optimal bidding strategy of power producers is proposed for a low voltage grid-connected microgrid (GCMG) system operating in a day-ahead electricity market having a pump storage (PS) unit as risk managing storage device. The uncertainties of PV and WT power plants are modeled through Latin hypercube sampling (LHS) based Monte Carlo simulations (MCS). The system performance has been investigated for three-generation scenarios of the renewable power generations. A penalty has been imposed on utilities for violating the committed power schedule in the day-ahead market based on the forecasted power generation. The optimal size of the storage system will help in avoiding the penalties imposed for deviations from the commitments. The optimum size of the PS unit has been obtained for the optimal bidding and minimizing the operational cost of the system. The results show that an appropriately sized PS unit is the best energy storage system to deal with the uncertainties of the DESs and reduce the operation cost up to 11.33–13.68% depending upon the operational constraints.
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