A multiple chance-constrained model for optimal scheduling of microgrids considering normal and emergency operation

Abstract Maintaining power balance under both normal and emergency conditions is one of the most important challenges in optimal scheduling of microgrids (MGs). In this paper, a multiple chance-constrained scheduling model is developed for optimal scheduling of microgrid considering the most important factors that affect the power balance of the MG such as the uncertainty of demand and renewable resources, sudden outage of distributed generators (DGs), and unwanted islanding. Due to the growing penetration and size of batteries, the outage of batteries is also considered. Simultaneous consideration of all above-mentioned factors complicates the scheduling problem. Hence, to reduce the complexity of the model, the chance constraints are reformulated innovatively by adding controllable variables to the chance constraints. In addition, to determine the required reserve in different conditions of MG operation (i.e. normal operation, outage of each DG, outage of each battery, and unwanted islanding), individual probability distribution functions (PDFs) are formulated. Based on these PDFs, a probabilistic index entitled probability of reserve sufficiency (PRS) is introduced. The model maintains a certain amount of PRS in different conditions of MG operation. Finally, the model is examined on a test microgrid for different case studies and the results are analyzed to evaluate the model.