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

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.