Affiliation:
1. CSG Electric Power Research Institute, Guangzhou 510663, China
2. Power Dispatching Control Center of Guangdong Power Grid Co., Ltd., Guangzhou 510062, China
Abstract
With the global pursuit of renewable energy and carbon neutrality, hydrogen-based microgrids have also become an important area of research, as ensuring proper design and operation is essential to achieve optimal performance from hybrid systems. This paper proposes a distributed control strategy based on multiagent self-triggered model predictive control (ST-MPC), with the aim of achieving demand-side control of hydrogen-based microgrid systems. This architecture considers a hybrid energy storage system with renewable energy as the main power source, supplemented by fuel cells based on electrolytic hydrogen. The primary objective of this architecture is aiming at the supply and demand balance problem under the supply and demand relationship of microgrid, the service life of hydrogen-based microgrid energy storage equipment can be increased on the basis of realizing demand-side control of hydrogen energy microgrid system. To accomplish this, model predictive controllers are implemented within a self-triggered framework that dynamically adjusts the counting period. The simulation results demonstrate that the ST-MPC architecture significantly reduces the frequency of control action changes while maintaining an acceptable level of set-point tracking. These findings highlight the viability of the proposed solution for microgrids equipped with multiple types of electrochemical storage, which contributes to improved sustainability and efficiency in renewable-based microgrid systems.
Funder
Science and Technology Project of China Southern Power Grid Corporation
Reference32 articles.
1. Optimal scheduling of grid-connected PV plants with energy storage for integration in the electricity market;Alba;Sol. Energy,2017
2. Trends in microgrid control;Olivares;IEEE Trans. Smart Grid,2014
3. Energy management strategies in hydrogen smart-grids: A laboratory experience;Valverde;Int. J. Hydrogen Energy,2016
4. Gu, W., Wu, Z., and Yuan, X. (2010, January 25–29). Microgrid economic optimal operation of the combined heat and power system with renewable energy. Proceedings of the IEEE pes General Meeting, Minneapolis, MN, USA.
5. On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid;Velarde;J. Power Sources,2017