In heating, ventilation and air conditioning (HVAC) systems of medium/high cooling capacity, energy demands can be matched with the help of thermal energy storage (TES) systems. If properly designed, TES systems can reduce energy costs and consumption, equipment size and pollutant emissions. In order to design efficient control strategies for TES systems, we present a model-based approach with the aim of increasing the performance of HVAC systems with ice cold thermal energy storage (CTES). A simulation environment based on Matlab/Simulink® is developed, where thermal behaviour of the plant is analysed by a lumped formulation of the conservation equations. In particular, the ice CTES is modelled as a hybrid system, where the water phase transitions (solid-melting-liquid and liquid-freezing-solid) are described by combining continuous and discrete dynamics, thus considering both latent and sensible heat. Standard control strategies are compared with a non-linear model predictive control (NLMPC) approach. In the simulation examples model predictive control proves to be the best control solution for the efficient management of ice CTES systems.

Energy efficient control of HVAC systems with ice cold thermal energy storage

BEGHI, ALESSANDRO;RAMPAZZO, MIRCO;SIMMINI, FRANCESCO
2014

Abstract

In heating, ventilation and air conditioning (HVAC) systems of medium/high cooling capacity, energy demands can be matched with the help of thermal energy storage (TES) systems. If properly designed, TES systems can reduce energy costs and consumption, equipment size and pollutant emissions. In order to design efficient control strategies for TES systems, we present a model-based approach with the aim of increasing the performance of HVAC systems with ice cold thermal energy storage (CTES). A simulation environment based on Matlab/Simulink® is developed, where thermal behaviour of the plant is analysed by a lumped formulation of the conservation equations. In particular, the ice CTES is modelled as a hybrid system, where the water phase transitions (solid-melting-liquid and liquid-freezing-solid) are described by combining continuous and discrete dynamics, thus considering both latent and sensible heat. Standard control strategies are compared with a non-linear model predictive control (NLMPC) approach. In the simulation examples model predictive control proves to be the best control solution for the efficient management of ice CTES systems.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/2795754
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