Two-Stage Robust Stochastic Model Scheduling for Transactive Energy Based Renewable Microgrids

Abstract

At present, the power system is developing toward a fully renewable energy resources (RERs) equipped system due to significant challenges with the conventional units. This trend has led to remarkable new challenges for power system planners considering the stochastic nature of RERs, application of new emerging technologies, etc. In this article, a two-stage robust stochastic programming model for the optimal scheduling of commercial microgrids equipped with 100% RERs to handle the existing uncertainties is presented. In the day-ahead electricity market, microgrids maximize their expected profits by optimizing their bidding strategy, while minimizing the imbalance cost is targeted for microgrids by adjusting the distributed energy resources in the real-time balancing market. Transactive energy technology is effectively applied to manage the energy trading between microgrids with each other in the local energy transaction market and with the power grid. For demand-side management, the demand response program is posed considering the shiftable and interruptible features of the load. Simulation results on the IEEE 33-bus standard system integrated with microgrids verify that the proposed model could provide satisfactory profits for microgrids participated in the energy exchanging process based on the transactive energy architecture.