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

Abstract

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