Efficient energy dispatch in multi-energy microgrids with a hybrid control approach for energy management system

The design of energy management systems (EMS) and dynamic control systems for multi-energy microgrids (MEMGs) combining diverse energy vectors (electricity, heating/cooling, and hydrogen) has not been extensively explored. Instead, prior research on MEMGs has predominantly focused on daily or weekly time horizons, adopting a static perspective primarily aimed at cost optimization or emission reduction. To address this gap, this article introduces a novel intelligent EMS based on fuzzy logic and model predictive control designed to minimize energy consumption within a MEMG while avoiding reliance on the main electrical grid. The MEMG comprises a photovoltaic power plant, a battery, electrical residential demand, a fuel cell, an electrolyzer, a hydrogen tank, a gas boiler, an electric boiler, an absorption chiller and thermal residential demand, with a connection to the main grid. By efficiently adjusting the operating points of thermal components based on renewable production and the available energy in the battery and hydrogen system, the MEMG achieves a synergistic integration of various energy vectors. The efficient energy dispatch leads to a 9.56 % reduction in operational costs, and a 2.82 % decrease in the CO2 emissions. Moreover, the findings demonstrate a notable reduction in the usage of both the gas boiler (by 2.82 %) and electric boiler (by 18.75 %), as well as the absorption chiller (8.91 %). Additionally, there is an increase in the state of charge of the electrical battery (by 21.43 %), hydrogen level (by 4.8 %), and state of energy (by 18.85 %). The results of this work thus highlight the adaptability and resilience of the presented EMS in establishing an effective intelligent energy dispatch among multiple energy vectors.