| description abstract | In contrast to building energy conversion equipment, less improvement has been achieved in thermal energy distribution, storage and control systems in terms of energy efficiency and peak load reduction potential. Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid and time-of-use electricity rates are designed to encourage shifting of electrical loads to off-peak periods at night and on weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building’s massive structure (passive storage) or by using active thermal energy storage systems such as ice storage. Recent theoretical and experimental work showed that the simultaneous utilization of active and passive building thermal storage inventory can save significant amounts of utility costs to the building operator, yet increased electrical energy consumption may result. The article investigates the relationship between cost savings and energy consumption associated with conventional control, minimal cost and minimal energy control, while accounting for variations in fan power consumption, chiller capacity, chiller coefficient-of-performance, and part-load performance. The model-based predictive building controller is employed to either minimize electricity cost including a target demand charge or electrical energy consumption. This work shows that buildings can be operated in a demand-responsive fashion to substantially reduce utility costs with marginal increases in overall energy consumption. In the case of energy optimal control, the reference control was replicated, i.e., if only energy consumption is of concern, neither active nor passive building thermal storage should be utilized. On the other hand, cost optimal control suggests strongly utilizing both thermal storage inventories. | |
