Efficient Energy Dispatch in Multi-Energy Microgrids with a Hybrid Control Approach for Energy Management System

Abstract

The design of energy management systems (EMS) and dynamic control systems of multi-energy microgrids (MEMGs) combining diverse energy vectors (electricity, heating/cooling, and hydrogen) has not been extensively explored. This paper presents a novel hybrid EMS combining fuzzy logic and model predictive control to optimize energy dispatch and reduce grid dependency in a gridconnected MEMG. It comprises for a photovoltaic power plant, a battery, an electrical residential demand, a fuel cell, an electrolyzer, a hydrogen tank, a gas boiler, an electric boiler, an absorption chiller and thermal residential demand. The synergy among energy vectors is achieved by adjusting the thermal component operation based on renewable production and storage levels. The findings show a notable decrease in gas (by 2.82%), electric boiler (by 18.75%), and absorption chiller (8.91%) usage compared to a conventional states-based EMS. The efficient energy dispatch leads to a 9.56% reduction in operational costs, and a 2.82% decrease in the CO2 emissions. Additionally, there is an increment in the levels of state of charge of the electrical battery (by 21.43%), hydrogen level (by 4.8%), and state of energy (by 18.85%). The results probe the adaptability and resilience of the suggested EMS in effectively managing multiple energy vectors.