Coordinated Operation of Electricity, Hydrogen, and Thermal Systems in a Residential Multi-Energy Microgrid
Author(s) -
Pablo Horrillo-Quintero,
Pablo Garcia-Trivino,
Ehsan Hosseini,
Carlos Andres Garcia Vazquez,
Higinio Sanchez-Sainz,
Luis M. Fernandez-Ramirez
Publication year - 2025
Publication title -
ieee transactions on industry applications
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 1.19
H-Index - 195
eISSN - 1939-9367
pISSN - 0093-9994
DOI - 10.1109/tia.2025.3618782
Subject(s) - power, energy and industry applications , signal processing and analysis , fields, waves and electromagnetics , components, circuits, devices and systems
Multi-energy microgrids (MEMGs) represent a specific typology of microgrids that combine multiple energy carriers—including electricity, heat, cooling, and hydrogen—within a coordinated framework. Existing studies emphasize energy dispatch optimization and often neglect real-time dynamic control. This paper presents a novel fuzzy-logic control method for the coordinated operation of electricity, hydrogen, and thermal systems in a residential MEMG. A photovoltaic (PV) power plant serves as the primary renewable energy source, while thermal sources include an electric boiler and a chiller. Additionally, a gas boiler is integrated to manage the hot water circuit. A hybrid energy storage system (HESS), comprising a battery and a hydrogen system, enhances operational flexibility. The fuzzy logic-based energy management system (FL-EMS) dynamically coordinates the interaction among energy systems based on renewable energy input and the state of energy (SOE) of the HESS. The proposed method is evaluated through simulations and hardware-in-the-loop (HIL) testing using OPAL-RT4512 and dSPACE MicroLabBox. The results show that the MEMG operates autonomously, with effective storage coordination and accurate thermal regulation. A sensitivity analysis confirms the robustness and adaptability of the FL-EMS, validating its suitability for real-time MEMG control. Compared to a machine-state-based EMS, the FL-EMS reduces the integral time-weighted squared error (ITSE) for temperature control by 49.38%, operating costs by 12.78%, and energy consumption by 15.05%.
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