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It is interesting to compare the results of the modeling with the actual measured results, due to the differences between the two, even given the additional load imposed by the water recycling system. The differrences point out the importance of the assumptions used in the modeling for occupant use intensity, scheduling and the impact of such technologies as occupancy sensors.
For the domestic hot water use, for example, the modeled demand was based on the population of the four school buildings and a reasonable assumption about how often hand-washing would be done in the library building. Actual use was very much less, perhaps because of time actually spent in the library compared to the other buildings.
Modeling software design can also affect results that differ from actual measurements. eQuest has difficulty modeling the effect of daylighting in interior zones, resulting in a predicted use of in- terior lighting even in the presence of daylighting from the roof. The daylight from the solar tubes in the center of the large interior space is apparently not being modeled appropriately with this software. In fact, actual measured lighting energy consumption is a small fraction of the modeled consumption (~0.2 kWhr/sf versus ~2.5 kWhr/sf).
In addition, the school’s culture of concern about sustainable buildings has led to lower use of electric lights than assumed in the model; while the model assumes continuous dimming, the library staff simply turn off the lights when the space is under-occupied. The same effect can be seen with the plug load category—half the use predicted by the model. While plug load is difficult to estimate without a detailed accounting of equipment to be used in the building, there is still a zealous use of the off-switch by the occupants.
It is interesting to note that the energy used by the water recycling system is approximately 8% of the total energy used in the building for all other occupant purposes. The system is used for all four buildings, so the amount of energy used is much larger than can be expected for a single- building system.
The end result of the actual use patterns is that the building (and its occupants) is performing at an exceptionally low EUI = 19.0 kBtu/sf-year, compared to the modeled number of EUI = 27.0 kBtu/sf-year. With the solar photovoltaic system sized to balance the latter annual number, the result is that the building is currently producing much more energy over the course of a year than it is consuming.
Energy Production versus Energy Use — Zero Net Energy Performance
On the basis of Site ZNE, as defined in the Introduction to this monograph, the results of the en- ergy measurements in the first year of occupancy indicate that the Stevens Library is performing better than ZNE. In fact, the solar photovoltaic system produced more energy at the end of one full year than the building was importing from the utility grid. It is performing as a net producer of renewable energy. The graph on the next page shows the energy produced each month by the building’s solar photovoltaic system compared with the energy used by the building. As ex- pected, there is energy being imported from the grid during the winter season and a net export of energy during the sunny summer period.
Another way to indicate ZNE is a cumulative energy production over the course of a year, as shown in the second graph on the following page. In this graph, the net production each month becomes the starting point of the following month’s net production amount. The curve goes down at first, since net production is negative in the winter, then starts to rise as there is more sun in the spring and summer, turning down again as the net production goes negative again as the fall and winter approach. For a ZNE building, the curve will just return to the zero point at the end of the year. As can be seen in the graph for Stevens Library, the curve is still above zero at the end of the year, indicating a net production of energy over the year.
Zero Net Energy Case Study Buildings: Volume 1
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STEVENS LIBRARY AT SACRED HEART SCHOOLS
CASE STUDY NO. 2
 





















































































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