Optimal operations for hydrogen-based energy storage systems in wind farms via model predictive control

Efficient energy production and consumption are fundamental points for reducing carbon emissions that influence climate change. Alternative resources, such as renewable energy sources (RESs), used in electricity grids, could reduce the environmental impact. Since RESs are inherently unreliable, during the last decades the scientific community addressed research efforts to their integration with the main grid by means of properly designed energy storage systems (ESSs). In order to highlight the best performance from these hybrid systems, proper design and operations are essential. The purpose of this paper is to present a so-called model predictive controller (MPC) for the optimal operations of grid-connected wind farms with hydrogen-based ESSs and local loads. Such MPC has been designed to take into account the operating and economical costs of the ESS, the local load demand and the participation to the electricity market, and further it enforces the fulfill-ment of the physical and the system's dynamics constraints. The dynamics of the hydrogen-based ESS have been modeled by means of the mixed-logic dynamic (MLD) framework in order to capture different behaviors according to the possible operating modes. The purpose is to provide a controller able to cope both with all the main physical and operating constraints of a hydrogen-based storage system, including the switching among different modes such as ON, OFF, STAND-BY and, at the same time, reduce the management costs and increase the equipment lifesaving. The case study for this paper is a plant under development in the north Norway. Numerical analysis on the related plant data shows the effectiveness of the proposed strategy, which manages the plant and commits the equipment so as to preserve the given constraints and save them from unnecessary commutation cycles. (c) 2021 The Authors. Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).

Automated summary

Efficient energy production and consumption are crucial for reducing carbon emissions that impact climate change. The integration of renewable energy sources in electricity grids can help reduce environmental impact. Proper design and operations are essential for achieving optimal performance from hybrid systems. The paper presents a model predictive controller for grid-connected wind farms with hydrogen-based energy storage systems, considering operating and economical costs, local load demand, participation in the electricity market, and enforcing physical and system dynamics constraints. The controller is designed to handle various operating modes of the hydrogen-based energy storage system and reduce management costs while increasing equipment lifespan. A case study in north Norway demonstrates the effectiveness of the proposed strategy in managing the plant and preserving equipment from unnecessary commutation cycles.