Risk-based Stochastic Scheduling of Resilient Microgrids Considering Demand Response Programs

Abstract

In this article, a risk-constrained stochastic framework is presented for joint energy and reserve scheduling of a resilient microgrid considering demand side management. The optimization problem is formulated to schedule the system operation in both normal and islanding modes by addressing the prevailing uncertainties of islanding duration as well as prediction errors of loads, renewable power generation, and electricity price. In a normal operation mode, where the grid-connection is available, the energy and reserve of local resources and energy trading with the main grid is scheduled to maximize the operator's profit considering feasible islanding. In a resilient operating mode, which is triggered by a disturbance in the main grid, the local resources should be scheduled to supply loads with the lowest emergency load shedding. To balance the economy and security requirements under uncertainties, the optimal scheduling is done properly through a security-constrained power flow method by considering system's objectives and constraints. Moreover, to properly handle the uncertainties of the problem, conditional value-at-risk metric is incorporated with the optimization model to control the risk of profit variability. The proposed scheme is implemented on a test microgrid and various case studies are presented to verify its effectiveness in normal and resiliency operating conditions.