Optimization of the Microgrid Scheduling with Considering Contingencies in an Uncertainty Environment

In this paper, a stochastic two-stage model is offered for optimization of the day-ahead scheduling of the microgrid. System uncertainties including dispatchable distributed generation and energy storage contingencies are considered in the stochastic model. For handling uncertainties, Monte Carlo simulation is employed for generation several scenarios and then a reduction method is used to decrease the number of scenarios. The scenarios are used in second stage of the stochastic model to check the system security. The amount of spinning reserve and energy are optimized in the first stage by minimizing the total cost of operation. A sample microgrid is used to compare the offered stochastic model with the deterministic one.