Intra-Hour Microgrid Economic Dispatch Based on Model Predictive Control

Renewable energy-based generation facilities emerging in microgrids are modifying many traditional principles of economic dispatch because of the variability and uncertainty of their output characteristics. Since the power generation from renewable resources is difficult to anticipate, a real-time adjustment of generation schedules is necessary after more forecast information becomes available. Intra-hour, or ultra-short-term dispatch, allows microgrid operators to frequently update generators' outputs for providing power supplies efficiently in an uncertain operating condition. However, several technical challenges such as information availability, control architecture, and computational burden make it difficult to find an optimal generation schedule at runtime. This work addresses the intra-hour economic dispatch problem by designing a closed-loop distributed model predictive control (DMPC) that reduces potential variations in the determined generation schedules. At first, optimization problems regarding the behaviors of several participants in a microgrid are formulated. Then, the procedures for achieving the real-time power balance under ramp-rate constraints are detailed. Simulation results present the efficiency of the proposed DMPC for the optimal intra-hour economic dispatch when multiple types of generation resources are considered in a microgrid.