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Current ProjectsAbu Dhabi Research ProjectsTechnologyLow-Lift-Optimized Plant, Advanced Transport, and Predictive Controls for Efficient Cooling
Low-Lift-Optimized Plant, Advanced Transport, and Predictive Controls for Efficient Cooling

Principal Investigators at MIT: Professors Leon Glicksman and Leslie K. Norford
Principal Investigator at Masdar Institute: Associate Professor Peter R. Armstrong

Description and Objectives

Cooling accounts for about 15% of energy use in modern buildings and represents a much higher percentage (20-30%) in warm climates. It is therefore imperative to address the world's cooling energy needs on two fronts: design buildings to reduce cooling loads and devise ways cool them more efficiently. This project will explore, assess, and demonstrate four highly complementary paths by which cooling systems can be made more efficient: (1) reduce motor, fan, pump, and compressor losses; (2) obtain closer heat-exchanger approach temperatures, (3) improve transport efficiency, and (4) make system and operational changes to reduce condensing temperatures and raise evaporating temperatures. The last path interacts in complex, and potentially extremely beneficial ways with the first three.

Approach

In this research, compressors, fans, and pumps are being characterized over a range of speed and loading conditions and the resulting information is being used to implement optimal chiller system controls for efficient cooling. The resulting chiller performance function is then used to further improve daily system performance by implementing a 24-hour look-ahead controller that improves load factor by precooling at night. The combination of improved load factor and optimal variable flow control results in substantial part-load efficiency improvements and energy savings. The same control and forecast capabilities can be used for highly effective demand response functions.

In order to properly implement load shifting, the controller must not only forecast internal gains and weather, but also maintain an accurate transient thermal response model of the conditioned space. Transfer functions representing the relation between temperature and heat rate trajectories and methods of identifying these transfer functions reliably from short-term observations are under development.

A modular chiller model has been developed from component models including chiller barrel, hydronic radiant distribution system, partially-wetted cooling/dehumidifying coil, condenser with desuperheating and subcooling sections, chilled water loop with variable-speed pump, condenser airflow loop with variable-speed fan, and variable-speed positive-displacement compressor. A semi-physical compressor model that reflects changes in refrigerant compressibility over a wide range of pressure ratio and inlet conditions, and that properly accounts for internal heat transfer and friction and flow losses over a wide range of shaft speed, has been developed. The chiller model converges to the simultaneous solution of fan, pump and compressor speed that achieves lowest cost system operation at any given cooling load and operating condition. A 24-hour look-ahead controller has been developed to determine the optimal precooling trajectory based on each day's forecast weather and occupant loading.

Simulation results indicate annual cooling system energy savings of 69-74% in climates ranging from temperate to hot and humid.

The foregoing modeling activities are being validated by assembling and testing prototype hardware in a calorimeter test bench and an existing MIT test room. Full-scale demonstrations will ultimately be conducted in Masdar City.

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