The hybrid-energy storage systems (ESSs) are promising eco-friendly power converter devices used in a wide range of applications. However, their insufficient lifespan is one of the key issues by hindering their large-scale commercial application. In order to extend the lifespan of the hybrid-ESSs, the cost functions proposed in this paper include the degradation of the hydrogen devices and the battery. Indeed, this paper aims to develop a sophisticated model predictive control strategy for a grid-connected wind and solar microgrid, which includes a hydrogen-ESS, a battery-ESS, and the interaction with external consumers, e.g., battery/fuel cell electric vehicles. The integrated system requires the management of its energy production in different forms, i.e., the electric and the hydrogen ones. The proposed strategy consists of the economical and operating costs of the hybrid-ESSs, the degradation issues, and the physical and dynamic constraints of the system. The mixed-logic dynamic framework is required to model the operating modes of the hybrid-ESSs and the switches between them. The effectiveness of the controller is analyzed by numerical simulations which are conducted using solar and wind generation profiles of solar panels and wind farms located in Abu Dhabi, United Arab Emirates. Such simulations, indeed, show that the proposed strategy appropriately manages the plant by fulfilling constraints and energy requests while reducing device costs and increasing battery life.

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.