Vermont School Studies Building Heating Efficiency
Putney Central School for grades K-8 is located in Putney, Vermont. The school has three wings, built in 1955 through 1964, 1974 and 1996, and is heated by three hot water boilers. Each wing is a separate heating zone, designated as Zones A, B and C.
Data loggers were used on each boiler oil burner to determine the daily operating time. The fuel splits were calculated by multiplying the burner operating time by the burner nozzle flow rate and the heating value of fuel oil. This fuel split was then converted to Btu/square foot (SF) - year (J) to determine the relative heating efficiency and fuel consumption in each of the three zones.
The fuel split was further converted to Btu/SF-year heating degree day (HDD). This calculation showed the relative heating efficiency adjusted to the HDD. If the number determined by this calculation is less than 5, then the heating efficiency of the building and the thermal efficiency of the envelope are good. If the figure is greater than 5, there is room for improvement. Further investigations are necessary to determine the factors contributing to higher figures.
An energy audit was carried out at Putney Central School in 2008. The building's energy performance was computer modeled using Trane Trace 700 software. The energy distributions of the zones between the computer model and those determined by data loggers were compared. It was found that the computer model used with the associated assumptions inaccurately predicted the building performance. The computer model deviated from the energy use determined by the data logger by 7% to 42%.
Use of data loggers
Motor run time data loggers were deployed on April 1, 2009 on boilers serving heating zones A, B and C at Putney Central School. The data loggers were removed on May 7, 2009.
Boiler A serves the gymnasium and a front wing built in 1957 and 1964. Boiler B serves a middle school that was built in 1974 and Boiler C serves a wing that was built in 1994. Boiler A has a 1-minute purge at the end of the firing cycle, which was subtracted from each burner run time.
Data analysis
Data analysis was performed for the coldest day of the period, April 13. The day had a maximum temperature of 39.3º F and a minimum temperature of 31.0º F.
The oil consumption for April 13, 2009 is shown in Table 1.
Extrapolated for the year with an annual oil consumption of 14,500 gallons, the breakdown of heating oil and heat load by school zone is shown in Table 2.
| Zone | Gallons | % |
| A | 45.3 | 65.5 |
| B | 12.9 | 18.7 |
| C | 10.9 | 15.8 |
| Total | 69.1 | 100.0 |
Table 1 Fuel splits between heating zones, April 13, 200
| Zone | % | Annual Gallons | Zone Square Feet | Btu/Sf-Yr | Btu/Sf-Yr-HDD |
| A | 65.5 | 9,500 | 26,219 | 50,000 | 6.9 |
| B | 18.7 | 2,710 | 3,120 | 119,900 | 16.7 |
| C | 15.8 | 2,290 | 12,212 | 25,900 | 3.6 |
| total | 100.0 | 14,500 | 41,551 |
Table 2 Heat loading by school zone.
Note: Square Feet is the area of heated space served by the boiler; Sf is square feet; Yr is year; HDD is annual heating degree days. For Putney, HDD is based on 7,200 annual heating degree days. Btu/Sf/Yr/HDD less than 5 indicates an efficient heating system. Btu/Sf/Yr/HDD greater than 5 indicates that improvements can be made to the heating and building envelope system.
Data interpretation
Boiler B in the middle school had the highest heat load per square foot of floor area at 16.7 Btu/Sf-Yr-HDD. The area served has a large exterior wall area relative to the floor area and contains an entry corridor with a large glass area. The efficiency of the boiler and overall heating system appears low.
Boiler A, serving the gymnasium and front wing, had the next highest heat load per square foot of floor area at 6.9 Btu/Sf-Yr-HDD. The boiler was oversized for the heat load and replacement should be considered. Insulation, ventilation, and air handler upgrades should be performed before replacing the boiler.
Boiler C, serving the new wing, had a heat load of 3.6 Btu/Sf-Yr-HDD, reflecting better insulation, thermopane windows, and a heat recovery ventilation system. This boiler appears to be oversized. Consideration should be given to using Boiler C to supply heat to the Boiler B area and removing Boiler B. Boiler C run times during the coldest part of the year should be reviewed before any changes are made to the heating system.
Data comparison to the computer model
The school was modeled using Trane Trace 700 software. A comparison of the actual building performance to the model is shown in Table 3 with annual fuel splits in %. The variance compares the actual performance of the data logger to the modeled performance.
| Zone | Modeled Fuel Split % | Data Logger Fuel Split % | Variance % Over (Under) |
| A | 52.2 | 65.5 | 24.8 |
| B | 20.1 | 18.7 | (7.0) |
| C | 27.4 | 15.8 | (42.4) |
Table 3 Comparison of modeled school performance with actual performance
As shown in Table 3, the modeled building performance per zone varies between 7% and 42% compared to the actual performance. Therefore, the model used in this example is not an accurate tool for predicting building performance. Energy saving measures based on the model would not reflect current and future building performance.
Conclusion
Data loggers were used to determine the fuel splits for three heating zones in a local school. The results were converted to a measure of building heating efficiency of Btu/SF-Yr-HDD. The zones varied from 3.6-16.7 Btu/SF-Yr-HDD.
A number less than 5 Btu/SF-Yr-HDD indicates a relatively efficient heating system and thermal envelope. A number greater than 5 Btu/SF-Yr-HDD indicates that improvements can be made to the heating system and thermal efficiency of the building. The low figure of 3.6 Btu/SF-Yr-HDD was found in a new building constructed in 1994 with an efficient insulation package, thermopane windows and heat recovery ventilation. The high figure of 16.7 Btu/SF-Yr-HDD was found for a school wing with large glazed areas, an entrance door with poor weather sealing, an inefficient boiler and a minimal insulation package.
The actual heat output of the building, as determined by data loggers, was compared to the computer modeled heat output of the building. The computer model deviated from the actual output by 7% to 42%.
Data loggers provide a simple and accurate method of determining actual building performance. They can be used to obtain baseline data on building performance. Based on this baseline data, suggestions for energy conservation measures (ECMs) can be made with real building information. Reductions in energy consumption through the installation of ECMs can then be measured and verified through the subsequent use of data loggers.