1. Eco-Dorm Retrofit Nadim Atalla, Emilia Chojkiewicz, Chris Jernigan,
Nick Kardous, Brigitte von Oppenfeld, Cassie Yuan 1

2. Reduce energy waste in Duke dormitories
Mission Statement:
Reduce energy waste in Duke dormitories 2

3. Approach Solar Fenestratio n 3
To begin this project, we obtained energy consumption data on Duke buildings from facilities management. Scrutinizing the data, we chose to focus on Gilbert Addoms. As a 60 year old dormitory, we observed high energy loss through fenestration, both through inefficient windows and orifices (see photo). Since we know duke is working towards sustainability, …. it makes no sense to incorporate renewable energy into an inefficient building, we first applied theoretical fenestration retrofits - a sealant for the holes, and a film for the windows. Then, once there was significantly less energy escaping from the building, we modeled a solar PVT system, to further reduce the building’s electricity consumption, which was high due to pre-existing inefficient air conditioning units. 3

4. Fenestration Analysis
Heat Conduction
Air Leakage
Solar Heat Gain
For fenestration, we calculated the net transfer of energy leaving GA through the windows (taking energy losses as positive). After approximating the number of windows, orifice size, and orientation of each window. We divided the fenestration analysis into 3 components: heat conduction, air leakage, and solar heat gain.
We applied this equation once without our fenestration retrofit, and once with the retrofit for comparison. We optimized this equation for summer!!
For fenestration, we developed an equation to model energy loss in the summer months when cooling is required, which we took to be March-August.
We used this equation to calculate the net transfer of of energy leaving GA through the windows, taking out as the positive direction.
It;s divided into 3 parts: conduction, leakage, heat gain.
We first approx. no. of windows, orifice size, and orientation of each window in order to apply this eqn. We applied it first without the retrofit as a baseline, and then w/ for comparison. 4

5. Heat Conduction Assumptions:
Double-paned, regular emissivity windows with air between panes
Uglass (provided by manufacturer) accounts for both conductance and radiation
We modelled the rate of heat transfer through the window using the heat conduction equation. This assumed double-paned, regular emissivity windows with air between the panes. The summer U-value was used and compared to the film U-value. 5

6. Air Leakage Assumptions: Steady, incompressible flow of air
Frictional losses are negligible
Weather tape reduces energy losses by 20%
We modelled air escaping through gaps in the windows as fluid moving through an orifice in order to calculate the mass flow rate of air.
Frictional losses were assumed negligible and the size of the orifice is standard for all windows. The leakage values were reduced by 20% once weather tape was applied. 6

7. Solar Heat Gain Assumptions: Extrapolated weather data is accurate
No losses due to shading
Only August insolation considered - 7

8. Solar Analysis Monthly solar electricity generated calculated by:
NREL’s System Advisor Model (SAM)
RDU weather data
Heat gained by thermal:
GA weather data 8

9. 9

10. Solar Analysis Efficiencies Assumptions 15% efficiency of PV
35% efficiency of thermal
0.5% electrical output loss per 1°C
Assumptions
100% efficiency in electricity transformation
100% efficiency of heat transfer through piping
Cycling water is at 21°C
63°C desired water temperature 10

11. Results - 11

12. Fenestration Results Annual energy saved from fenestration retrofit:
45,000 kWh
After calculating the energy loss due to fenestration in the building from the net heat transfer equation I introduced earlier, a SEER value of 10 for AC units and 11.5 for chilled water was applied to the data. Our final result was 45,000 kWh of cooling energy saved over the course of a year. You can see the energy savings by side in the chart here. As you can see, the energy savings per side depend on the number of windows on each side and the orientation of the windows. Southern facing windows resulted in the highest energy savings. 12

13. Insolation Model Results
Solar Results
Insolation Model Results
7300 kWh 13

14. Viability Testing 14

15. Fenestration Viability Testing
Actual energy use summer 2016 (kBtu)
1,670,000
% Energy loss due to fenestration
54.4 %
Energy saved from fenestration retrofit over the summer (kBtu)
153,000
Energy saved from fenestration retrofit over the summer (kWh)
45,000
% Energy saved
16.9 %
-The actual energy use for GA from March-August was about 1.7 million kBTU
-Our results from our fenestration model only accounted for 54% of this energy use
-Since we did not account for heating or lighting, this is likely a reasonable approximation for energy loss due to fenestration
-We saved about 17% energy by applying our fenestration retrofit, which is also a reasonable percentage, although it is a little low. Further analysis might result in higher energy savings. 15

16. Film Testing 16

17. 17

18. Solar Viability Testing
Total Energy Production
Insolation Model
7100 kWh
SAM
7300 kWh 18

19. Economic Impact Annual energy saved from fenestration retrofit
45,000 kWh
Money Saved
$3,350
Total cost
$21,340
# of years to break even
6.4
Annual energy saved from solar retrofit
15,700 kWh
Money Saved
$1,200
Total cost
$33,700
# of years to break even
28.8
Some other associated economic impact not listed here:
+Businesses and homeowners are eligible for a 30% tax credit if they install solar panels on their property. That's been in place since 2006 but in December Congress renewed the tax credit for another six years. That lowers installation costs considerably.
+solar equipment costs are down nearly 70% since 2010
-Short-term headwind: cheap oil and gas prices
-Not local 19

20. Environmental Impact
a reduction in emissions of carbon dioxide or greenhouse gases made in order to compensate for or to offset an emission made elsewhere. 20

21. Conclusions 21

22. Next Steps
Recalculating results with regular PV panels instead of the overly sophisticated PV/T
Expand fenestration model to include winter for more accurate approximation of annual energy savings
Sharing findings with Facilities Management to assess implementation feasibility 22

23. Acknowledgements
Tavey Capps Casey Collins Jason Elliott Chisato Gomez Chris Dougher Dr. Emily Klein Dr. Josiah Knight
content/uploads/2016/06/Solimpeks-IOM.pdf
content/uploads/2016/06/Eurofin-Testbericht- VOLTHER-Powervolt.pdf 23