scope:

INTRODUCTION

Shifting building cooling loads using thermal energy storage (TES) systems provides several advantages including reduction of peak demands for the electrical utilities and reduction of operating costs for the building owners. Generally, two types of TES systems are typically utilized in buildings: passive and active.

Passive TES systems utilize precooling strategies of the building thermal mass during nighttime to shift and reduce peak cooling loads (Braun 2003). Simulation analyses of various precooling strategies have shown that energy cost savings of 10% to 50% and peak demand reductions of 10% to 35% are possible by utilizing a preconditioning control strategy (Braun 1990, Rabl and Norford 1991, Conniff 1991, Andreson and Brandemuehl 1992, Morris et al. 1994, Keeney and Braun 1996, Chen 2001, Braun et al. 2001, Chaturvedi and Braun 2002). Experimental studies have also shown comparable levels of cost savings and peak demand reduction (Braun et al. 2001, Keeney and Braun 1997, Morris et al. 1994). Control optimization geared toward specific outcomes can generally increase cost savings or peak demand reduction (Braun 2003).

Active TES systems refer to the use of chilled water or ice tanks on the plant chilled water loop as a heat storage medium. Active TES systems provide load shifting by allowing the chiller plant to be run during unoccupied periods, storing the heat absorption capacity, and discharging it during occupied and/or peak periods to reduce the need for mechanical cooling of the chilled water loop. Chilled water tanks and ice storage tanks are the most common active TES equipment. The dispatchable load shifting capacity with active TES systems allows for a reduction in chiller size due to a reliable reduction in peak loads, and the lower chilled water supply temperature allows for unique airside HVAC designs (Henze and Krarti 2002). Several control strategies have been proposed for active TES systems including chiller-priority, storage-priority, constant-proportion, and optimal controls (Henze 2003). While some active TES systems in the field have been found to be underperforming (Guven and Flynn 1992, Tran et al. 1989), these systems have demonstrated overall cost savings and increased energy consumption compared to systems without active TES (Sohn 1991, Henze and Krarti 1998, Ihm et al. 2004). Simulation work on optimal control of active TES has shown that it is possible to reduce costs by as much as 20% without increasing overall energy consumption (Henze and Krarti 1998).

The combined utilization of passive and active TES systems has been investigated and found to be capable of reducing costs by up to 45% when optimal controls are considered (Henze and Krarti 2002, Henze et al. 2004, Zhou et al. 2005, Krarti et al. 2007).

In this paper, the performance of combined passive and active TES systems is investigated through field testing of various control strategies. The field testing is carried in an elementary school in Colorado equipped with an ice storage system. A simulation environment based Energyplus (Crawley, 2000), a detailed whole-building simulation program is used to determine the optimal control strategies (Zhou et al. 2005, Krarti et al. 2007). First, the building and its cooling system is presented. Then, the testing procedures as well as the simulation environment are briefly outlined. Finally, the testing results are summarized and discussed.