Demand Shifting with Thermal Mass

The principle of pre-cooling and demand limiting is to pre-cool buildings at night or in the morning during off-peak hours, storing cooling in the building thermal mass and thereby reducing cooling loads during the peak periods. Savings are achieved by reducing on-peak energy and demand charges. The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies.

In Summer 2003, a pre-cooling case study was conducted at the Santa Rosa Federal Building. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort range (70°F) during the occupied hours before the peak period and floating the zone temperatures up to the high end of the comfort range (78°F) during the peak period. With this strategy, the chiller power was reduced by 80 to100% (1 to 2.3 W/ft²) during peak hours from 2 pm to 5 pm without having any thermal comfort complaints submitted to the operations staff.

Although the initial study was quite successful, some key questions remained unanswered, including: What was the actual comfort reaction? What is the effect of extended (nighttime) pre-cooling on the following day peak shed? What will happen in really hot weather?

In order to address these questions, field tests were performed in two buildings in 2004. In addition to further testing at the Santa Rosa Federal Building, tests were performed in a medium size office building in Rancho Cordova (McCuen Center One Building). A key feature of the 2004 study was the comfort survey. A web-based comfort survey instrument was developed and used in the field tests to assess thermal sensation, comfort and productivity ratings in these two buildings. To supplement the field tests, EnergyPlus computer simulation models were built for the two buildings and used to estimate the impact of various pre-cooling strategies on peak demand. In addition, a set of buildings were audited to assess their suitability for pre-cooling in terms of their building materials and control system and the willingness and ability of the building staff to implement pre-cooling strategies. These audits provide a preliminary assessment of customer acceptability and market readiness of pre-cooling.

The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft² office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month.

It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1 – 2.3 W/ft²) during normal peak hours from 2 – 5 pm, without causing any thermal comfort complaints. The effects on the demand from 2 – 5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

This paper describes development of an inverse building model and its application in studying the performance of a demand-limiting (DL) control strategy. The demand-limiting strategy involves precooling (PC) a building during unoccupied times, maintaining the zone temperature setpoints at the lower limit of comfort during off-peak, occupied periods, and then limiting the peak cooling rate to a target for on-peak, occupied times that keeps zone conditions within comfort limits. Data from the Iowa Energy Center (IEC), which is typical of small commercial buildings, were used to train an inverse model that was then employed as a tool to evaluate the potential for peak load reduction through control of building thermal mass. The potential for demand limiting was investigated through parametric analysis compared with night-setup (NS) control.

This paper provides an overview of research related to use of building thermal mass for shifting and reducing peak cooling loads in commercial buildings. The paper presents background on the concept and the problem of optimizing zone temperature setpoints and provides specific results that have been obtained through simulations, controlled laboratory testing, and field studies. The studies have demonstrated significant savings potential for use of building thermal mass in commercial buildings. However, the savings are sensitive to many factors, including utility rates, type of equipment, occupancy schedule, building construction, climate conditions, and control strategy. The paper also attempts to provide an assessment of the state of the art in load control using building thermal mass and to identify the steps necessary to achieve widespread application of appropriate control strategies.

A tool was developed that allows evaluation of thermal mass control strategies using HVAC utility costs as the baseline for comparison. Inverse models are used to represent the behavior of the building, cooling plant, and air distribution system. Inverse models use measured data to "learn" system behavior and provide relatively accurate site-specific performance predictions. Based on weather and solar inputs, as well as occupancy and internal gains schedules and utility rates, the evaluation tool predicts the total HVAC utility cost for a specified control strategy. Intelligent thermal mass control strategies can then be identified in a simulation environment using this analysis tool. The evaluation tool was validated using data collected from a field site located near Chicago, Illinois. The tool predicted HVAC utility costs for a summer month billing period that were within approximately 5% of actual costs. Additional studies were performed to examine the utility savings potential for summertime operations at the field site using various thermal mass control strategies. The best strategy resulted in approximately a 40% reduction in total cooling costs as compared with night setup control. Simulation studies were also used to analyze the overall impact of location on the savings potential for use of building thermal mass. Representative utility rates for five locations (Boston, Chicago, Miami, Phoenix, and Seattle) were used along with the models obtained for the field site. Significant savings were achieved in all locations except Seattle.

A building cooling control strategy was developed and tested for a 1.4 million square foot (130,000 square meter) office building located in Hoffman Estates, IL. The goal of the control strategy was to utilize building thermal mass to limit the peak cooling load for continued building operation in the event of the loss of one of the four central chiller units. The algorithm was first developed and evaluated through simulation and then evaluated through tests on two identical buildings. The east building utilized the existing building control strategy while the west building used the precooling strategy developed for this project. Consistent with simulation predictions, the precooling control strategy successfully limited the peak load to 75% of the cooling capacity for the west building, while the east building operated at 100% of capacity. Precooling of the building mass provided an economical alternative to the purchase of an additional chiller unit. The estimated cost of installing an additional chiller was approximately $500,000. Computer models developed for this project also showed that precooling based upon cooling cost minimization could result in savings of approximately $25,000 per month during the peak cooling season. The building model was validated with experimental results and could be used in the development of a cost minimization strategy.

This paper describes an investigation into the use of building thermal capacitance as a means of reducing the operating costs associated with maintaining adequate comfort conditions in buildings (termed "dynamic building control"). The state of the building thermal storage can be controlled through variations of the zone temperatures over time within the thermal comfort region. The primary opportunities in varying zone setpoints in an optimal fashion are associated with shifting cooling loads from daytime to nighttime to (1) reduce peak electrical demands, (2) take advantage of low nighttime electrical rates, (3) offset mechanical cooling with "free" cooling at night, and (4) enhance equipment operation at more favorable part-load conditions. The approach utilized in this study was to apply dynamic optimization techniques to computer simulations of buildings and their associated cooling systems for a range of conditions in order to determine the maximum possible savings. Results indicate that both energy costs and peak electrical use can be significantly reduced through optimal control of the intrinsic thermal storage within building structures. However, the cost savings depend strongly on several factors including 1) utility rate structure, 2) part-load characteristics of the cooling plant and air handling system, 3) weather,4) the occupancy schedule, and 5) building thermal capacitance.