Impact of thermal stores on multi-energy microgrids with multi-layer dynamic control architecture

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks Pub Date : 2025-02-25 DOI:10.1016/j.segan.2025.101667

Pablo Horrillo-Quintero , Iván De la Cruz-Loredo , Pablo García-Triviño , Carlos E. Ugalde-Loo , Luis M. Fernández-Ramírez

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引用次数: 0

Abstract

Thermal energy storage systems (TESSs) enhance multi-energy microgrids (MEMGs) operation by optimizing energy management. While previous research primarily focused on optimizing the MEMG operation using static MEMG models, this paper analyzes the dynamic impact of TESS on a grid-connected residential MEMG. This includes a photovoltaic plant, an electrical battery, and a hydrogen system with an electrolyzer, a fuel cell, and hydrogen tank. The thermal subsystem includes a gas boiler, a micro-combined heat and power (CHP) unit, an electric boiler, and a TESS tank. A novel intelligent control architecture based on fuzzy logic, model predictive control, and nonlinear optimization is presented to control the MEMG. Simulation results with TESS reveal a balanced heat production and demand, and improved temperature control. The integral time squared error (ITSE) is reduced by 91 % for the hot water circuit control and 81 % for the overall thermal balance of the MEMG. The improved control scheme also reduces the gas consumption, with a reduction of 12.44 % for the gas boiler, 1.81 % for the CHP, and 8.66 % in total, leading in turn to reduced operational costs (by 6 %) and CO₂ emissions (by 8.37 %) compared to the MEMG operation without a TESS under the same control scheme.

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来源期刊

Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology

CiteScore

7.90

自引率

13.00%

发文量

206

审稿时长

49 days

期刊介绍： Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.