A Coordinated Multitimescale Model Predictive Control for Output Power Smoothing in Hybrid Microgrid Incorporating Hydrogen Energy Storage

Abstract

The intermittency of renewable energy sources (RESs) leads to the incorporation of energy storage systems into microgrids (MGs). In this article, a novel strategy based on model predictive control is proposed for the management of a wind-solar MG composed of RESs and a hydrogen energy storage system. The system is involved in the daily and regulation service markets, characterized by different timescales. The long-term operations related to the daily market are managed by a high-layer control, which schedules the hydrogen production and consumption to meet the load demand, maximizes the revenue by participating in the electricity market, and minimizes the operational costs. The short-term operations related to the real-time market are managed by a low-layer control (LLC), which corrects the deviations between the actual and forecasted conditions, by optimizing the power production according to the participation in the market and the short-term dynamics and constraints of the equipment. In addition, the LLC is in charge of smoothing the power provided to the grid. Numerical simulations demonstrate that the strategy effectively operates the MG by satisfying constraints and energy demands while minimizing device costs. Moreover, when compared to other strategies, the controller yields fewer state switches in the hydrogen devices, thus extending their lifespan. The efficacy of the control strategy is further validated through a lab-scale MG setup.