RT journal article
T1 Dynamic Fuzzy Logic Energy Management System for a Multi-Energy Microgrid
A1 Horrillo Quintero, Pablo
A1 García Triviño, Pablo
A1 Hosseini, Ehsan
A1 García Vázquez, Carlos Andrés
A1 Sánchez Sainz, Higinio
A1 Ugalde Loo, Carlos E.
A1 Péric, Vedran S.
A1 Fernández Ramírez, Luis Miguel
A2 Ingeniería Eléctrica
K1 Electricity
K1 Energy management system
K1 Energy storage system
K1 Fuzzy-logic
K1 Multi-energy microgrids
K1 Thermal
AB While multi-energy microgrids (MEMGs) offer a promising approach to reduce energy consumption through coordinated integration of various energy vectors, research has primarily focused on static studies. These studies aim to optimize a particular cost function but neglect the dynamic aspects of the system operation. This paper presents a dynamic model of an MEMG comprising of electricity and thermal vectors. A novel dynamic fuzzy logic-based energy management system (EMS) is investigated, aiming to ensure energy balance (electric and thermal), optimize renewable energy utilization, and reduce the reliance on the local electricity grid and gas. Both the EMS and MEMG have been evaluated under different weather conditions and a 4-hour variable load profile. Furthermore, the EMS effectiveness has been verified through a real-time experiment using an OPAL-RT4512 unit and a dSPACE MicroLabBox prototype. The results show that the proposed fuzzy logic-based EMS outperforms a conventional EMS based on machine states (statesbased EMS), achieving a notable reduction in electricity grid consumption of 80%, as well as a consumption reduction of 7.4% in the gas boiler and 5.4% in the electric boiler. Furthermore, the control performance results in a remarkable reduction in ITAE (42.57%), ITSE (89.10%), IAE (54.36%) and ISE (57.55%) for the hot water temperature control, and in ITAE (17.06%), ITSE (52.50%), IAE (31.19%) and ISE (29.99%) for the heating control
PB IEEE - Institute of Electrical and Electronics Engineers INC
YR 2024
FD 2024
LK http://hdl.handle.net/10498/33979
UL http://hdl.handle.net/10498/33979
LA eng
NO This work was supported in part by the Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación, and Unión Europea‘‘NextGenerationEU/PRTR’’ (Grant TED2021-129631B-C32 supported by MCIN/AEI/10.13039/501100011033 andNextGenerationEU/PRTR)
DS Repositorio Institucional de la Universidad de Cádiz
RD 09-may-2026