Solar Photovoltaic Suitability for the Campus of the
University of North Carolina at Chapel Hill
Stewart Edie, Tyler Evans, Noah Kittner, Ashley Mui
December 6th, 2010
Geography 491
Abstract
In 2007, Chancellor Moeser signed the Presidents’ Climate Commitment, pledging to
reduce the University of North Carolina’s carbon emissions by 80% before 2050. One simple
solution to reducing CO2 emissions is to increase the installation of renewable energy on
campus. Solar electricity generated from photovoltaic cells is one of the most feasible renewable
energy technologies. The goal of this study is to determine suitable locations on UNC’s campus
where photovoltaic rooftop arrays could be placed in order to maximize electricity generation.
We classified rooftops based on a threshold of incoming solar radiation with respect to shading,
rooftop area, elevation and UNC’s latitude and longitude. The Area Solar Radiation tool built
into ArcGIS calculated the total annual incoming solar radiation that campus rooftops received
based on our GIS topographical analysis raster. The potential electrical output was calculated
using these insolation and solar panel efficiency values. Estimates of potential savings were then
calculated using reasonable, commercially available polycrystalline panel prices and local
electricity rates. Our analysis found parking decks and larger buildings like Woollen Gymnasium
and Davis Library to be prime candidates for photovoltaic implementation on campus. Possible
annual savings ranged from $1K per year to $10M a year on the most productive rooftop.
Objectives
The objective of this study is to determine suitable rooftop locations at UNC-Chapel Hill
for photovoltaic installations through GIS analysis. We also calculate affordability with regard
to potential electricity savings and payback periods for installations on different campus
buildings. Overall, this project determines the viability of solar electricity as an option for
alternative energy on the UNC campus by highlighting sites on campus with the highest potential
for solar electricity production.
Background
Currently, UNC powers its campus through a coal-fired co-generation power plant
supplemented by electricity from Duke Energy. This co-generation system operates at a higher
efficiency than average coal power plants because it reuses the steam from electricity production
for campus heating. Despite the higher efficiency of this power plant, much of this coal is
produced from environmentally degrading Appalachian surface mines. As the UNC demand for
energy increases with operational facilities and student population growth, it may be in UNC’s
best interest to switch to alternative forms of electricity. UNC does not produce enough
electricity at the co-generation plant to completely power the University. During 2009-2010,
UNC consumed 308 GW-hr of electricity, with nearly 75% of electricity purchased from Duke
Energy at different contracted rates (UNC Energy Management). If UNC were to produce more
of its own electricity, it would evade volatile energy prices in the future and determine its own
sources of energy.
The 2008 renewable energy project to install solar thermal panels on Morrison Residence
Hall helped the building win the EPA National Building Competition by saving the University
money in heating costs for the ten-story dormitory. This project serves as a model for other on
campus renewable energy projects. As a large force in the community, UNC could set a positive
example of environmental stewardship and energy efficiency by considering solar electricity as a
major source of alternative energy.
Data Acquisition and Methodology
A bare earth digital elevation model of Orange County provided by the North Carolina
Department of Transportation serves as the base map for this project. The bare earth DEM was
generated from LiDAR obtained in April of 2007. The bare earth DEM is in the North Carolina
State Plane NAD83 coordinate system with a spatial resolution of 20 feet. All subsequent
layered data sets were converted to this coordinate system and a spatial resolution of 20 feet was
maintained throughout our analysis.
Initially, we clipped the DEM to the area of the University of North Carolina campus to
reduce data volume and to decrease the computation time associated with calculating potential
insolation. The corrected bare earth DEM does not include buildings and trees in the
topography. Neighboring buildings and trees are the most influential insolation shading factors
on building rooftops. We gathered a shapefile from UNC Mapping and Geographic Information
Services that maps the footprints of all campus buildings. The building shapefile also attributes
the highest rooftop elevation of the individual buildings to their respective footprints. Only 146
of the 612 buildings in the building shapefile had an assigned building elevation. Therefore, we
could only include the buildings with known building elevations in our analysis. Those
buildings with an assigned building elevation were converted from vector to raster format with a
20 foot cell size to match the DEM. Each cell in the converted building raster was assigned to its
respective building’s elevation. We merged the bare earth DEM with the building raster to add
building height to the topography.
To add trees to the DEM, we obtained a point file of trees on the UNC campus from
UNC Mapping and Geographic Information Services. Within this point file, we selected trees
that are within 30 feet of our campus building data set and are taller than their neighboring
building, using a buffer analysis. The selected trees were converted to raster format with a 20
foot cell size. For those trees that occupy the same 20 ft raster cell in the DEM, only the tree
with the greatest height was used in the raster conversion. This prevented the raster conversion
from assigning the cumulative sum of all tree heights within a 20 ft raster cell as the value of the
new cell. Figure 1 is the result of the merge between the tree raster and the bare earth/building
DEM.
Figure 1: Bare earth DEM that includes the height of UNC campus buildings and
neighboring tree heights in the topography.
We used the final tree, building, and bare earth DEM and the Area Solar Radiation Tool
in the Spatial Analyst package to determine potential insolation for the UNC campus. The
incoming solar radiation model was run for 35.9º N for a one year (2010) period with monthly
intervals using a uniform clear sky. The tool produced a 20 ft cell-size raster with cell values
assigned to potential annual insolation, shown in Figure 2
.
Figure 2: The annual area insolation for the UNC campus.
Analysis and Results
Our study area spans nearly three million square feet of rooftop, composing an expansive
area available for photovoltaic installations. This analysis identifies and ranks buildings with
regard to incoming solar radiation. The amount of incoming solar radiation is ultimately the
determining factor in predicting potential solar electricity generation.
We overlayed the shading incorporated insolation raster with the UNC campus buildings
shapefile and used the zonal statistics tool to calculate the total potential insolation for each
building. The zonal statistics tool summed the potential insolation within each building’s
defined boundary. We attributed the resulting potential insolation values to each building in the
UNC campus buildings shapefile. We reclassified the data into seven classes using a natural
breaks distribution ranging from very low insolation to very high insolation. Initially, we
observed a positive correlation of rooftop area to potential insolation. For example, very large
rooftops naturally had large annual rooftop insolation values because of their large area. Smaller
buildings that may receive a large amount of insolation relative to their size were overshadowed
by the buildings with larger rooftops. We removed this bias from the data by generating an
“insolation density” per rooftop, calculated by dividing the annual insolation received by the area
of the rooftop. To do this, we added a field to the insolation dataset containing this calculation.
This allowed us to differentiate high insolation rooftops from low ones regardless of rooftop size.
Figure 3 gives the normalized potential insolation per rooftop.
Figure 3: Potential insolation normalized by rooftop area on the UNC campus.
Based on Figure 4, the South Campus buildings on campus generally receive more
incoming solar radiation than North Campus buildings. This spatial distribution is due to the
higher elevation, southern aspect, and larger roof area of the South Campus buildings, as well as
the absence of trees on South Campus. Shading represents a key issue when considering
photovoltaic installations on North Campus buildings. Davis Library is an exception to the
potential energy production trends of North Campus buildings. Its height and large rooftop area
overcome the effect of shading induced by trees and neighboring buildings.
To generate the final rooftop insolation density dataset shown above, the effects of
shading were incorporated using GIS tools. One important aspect of shading was the physical
presence of trees that block sunlight due to their height and canopy density. Figure 4 shows the
density of trees surrounding North Campus buildings to be greater than the density of trees
surrounding South Campus buildings. The difference in density of trees is also seen in the
difference in potential insolation for building rooftops on North and South campus. Trees have a
larger impact on North Campus as evidenced by the low and very low potential insolation for
buildings near Polk and McCorkle quads in Figure 4. One exception to this trend is Fetzer Gym
in the center of campus. The density of trees surrounding the gym is high, but the potential
insolation for the gym is also high. It is likely that the trees surrounding the gym are not
considerably taller than the height of the gym and therefore do not provide significant shading on
the rooftop. The historic nature of North Campus requires old trees in order to maintain its
aesthetic beauty whereas the much newer South Campus clear-cut trees in order to build more
buildings. Future solar installation planners should incorporate tree shading into their plans in
order to maximize the incoming solar radiation.
Fetzer Gym
Figure 4: Tree impact on rooftop potential energy.
Discussion
Overall, the UNC campus rooftop network provides ample space for solar panel arrays
and receives a significant amount of annual incoming solar radiation. This analysis suggests that
with capital investment in panels covering only 25% of the roof area, 39 GW-hr of electricity
could be displaced per year from state-of-the-art solar panels, about 10% of UNC’s current
energy demand. While initial high costs may discourage investors, the steady returns for at least
30 years could reduce campus electricity costs for the future. Assuming a purchasing agreement
between Duke Energy and the campus continues, the freedom for UNC to produce its own
energy would insulate UNC from unpredictable energy prices. The past two years saw energy
prices soar 45% and 58% respectively (UNC Energy and Water Report 2010).
The 2007 renovations of Morrison residence hall brought solar thermal panels to UNC’s
campus. The installation capitalized on pre-existing renovation plans, therefore logically
explaining the location choice. Morrison recently gained national attention for winning an
energy saving competition. This success could inspire and motivate future renovations in similar
residence halls. A more nuanced decision making process based on incoming solar radiation
would better suit the similarly designed and structured South Campus residence halls Ehringhaus
and Craige. Ehringhaus’ proximity to the baseball stadium, a low topographic area with no trees,
and southern facing roof make it a prime location for photovoltaic installation based on our
spatial analysis.
Typical photovoltaic site designers consider rooftops as prime real estate for solar panel
installations because of their high elevation and large areas. Based on Figure 2, rooftops are
distinguished as suitable locations because of their high values of incoming solar radiation
relative to the ground level. The blue areas surrounding many buildings expose the shadow
induced by neighboring buildings. The large hospital wings and athletic centers on South
Campus are easily distinguished from the smaller and more shaded buildings on North Campus.
If the University installed solar electricity to feed into its electricity grid, the
financial savings could be in the millions of dollars. UNC currently purchases electricity from
Duke Energy at nearly $0.06/kWh and buys electricity by the bulk, which implies that the
university pays a premium if the demand exceeds the planned amount of electricity (Strategic
Energy and Water Plan, 2010). While photovoltaic panels may carry initial capital costs that
drive away potential investors, the returns on a large scale would allow the University to allocate
money toward more academic expenses than energy costs. Figure 5 maps the potential annual
energy monetary savings per building. These savings were determined by translating the
potential incoming solar radiation per building into monetary savings produced by solar
electricity. The potential incoming solar radiation was initially multiplied by the efficiency of a
solar panel array (8%). Then, the radiation was multiplied by the coverage area of the panel
arrays, which we assumed to be 25% of the rooftop area. The resulting energy output per
building in kilowatt-hours was then multiplied by the average cost of fossil fuel generated
electricity ($0.06/kWh) to determine the amount of money saved by producing solar electricity.
From Figure 5, our analysis exhibits a photovoltaic installation on top of Dogwood Parking Deck
alone could save the university between $6.6-9.9 million.
Figure 5: Annual savings per UNC campus building in dollars.
Figure 6 gives several suitable locations on campus for photovoltaic panel installation.
We considered suitable locations for solar panel installation to be the buildings with medium-
high, high, or very high potential insolation values as seen in Figure 4. These buildings would
provide the most economic electricity generation. The most significant of these sites are the
Craige and Dogwood parking decks, with potential outputs of 65000 and 164000 MW-hr
respectively, as they have the largest area rooftops, and are tall enough to avoid any shading
effects. These two buildings could provide the campus with the most solar electricity generation,
but it may not be economically feasible to construct a roof over the top of these structures to
support a solar panel array. Furthermore, our analysis suggests that Craige and Ehringhaus
Dorms are suitable locations for solar electricity, receiving more insolation per year than
Morrison Dorm, which already has solar thermal installation. This is interesting because if it
were possible to receive funding to install panels on Morrison, one of the least suitable of the
South Campus dormitories, it should be possible gain funding to install panels on more suitable
dormitories in the future. In addition, Davis Library could provide a maximum output of about
39000 MW-hr in a year, and is one of the most favorable sites for solar energy with its high
elevation and large rooftop area. We consider Davis Library to be the best site for solar panel
installation. Davis Library experiences significant incoming solar radiation per year, has a
relatively flat rooftop, and is tall enough that the solar panels would be hidden from eyesight,
avoiding the common opinion that solar panels are unsightly. Finally, certain small buildings on
campus still prove suitable for future photovoltaic installation such as Rosenau Hall (4000 MWhr), Lenoir Hall (3000 MW-hr), and Phillips Hall (8000 MW-hr). Due to the smaller installation
cost associated with smaller buildings, these sites could still be successful, despite the decreased
solar insolation per year. In order to further progress green energy on campus, smaller, cheaper
projects could be ideal “experimental” trials to assess the success of photovoltaic energy
production.
Figure 5. Potential Buildings for Photovoltaic Installation.
The following table shows examples of the highest performing rooftops classified in terms of
their rooftop areas. The number of panels assumes 25% roof coverage.
Table 1: Selected Sites on Campus for Photovoltaic Installation
The payback periods for each building were calculated by dividing the cost of the panel
installation by the monetary value of the electrical energy the installation produces. This study
does not account for the additional infrastructural costs and other requirements that a large scale
installation may require. It does include has estimated the cost of the panels, the price of the
inverter, and the cost of installation labor.
CO2 Emissions Avoided
Policy makers seeking to decrease greenhouse-gas emissions look to low emitting, clean
types of energies like solar power to replace coal fired plants. Duke Energy spews 518 gCO2/kWh into the atmosphere and the only carbon dioxide emissions from solar electricity occur
from the production, installation, and disposal of the panel. During electricity production, there
are no CO2 emissions. Assuming PV panels over their life emit about 50 g-CO2/kWh, UNC
could drastically reduce its emissions by displacing dirty electricity. Equipping all potentially
suitable sites with photovoltaic panels on campus could at the most displace 440 kilotonnes of
CO2 per year. While such savings may not be feasible, offsets for installations spanning 25% of
the rooftop for Davis and Fetzer average around 20 kilotonnes of CO2 annually. In 2009, the
UNC Greenhouse Gas Emissions Inventory documented that UNC’s campus emitted 452
kilotonnes of CO2. Therefore investing in photovoltaic energy on a large scale could also
provide a mitigation scheme to become carbon neutral.
Conclusion
Our analysis demonstrated the Dogwood Parking Deck, the Craige Parking Deck, Davis
Library, and Woolen Gym to be suitable sites for photovoltaic electricity production based on
size and annual solar radiation. The total energy savings that the panels could produce if all
campus buildings were covered could produce is $51 billion, compared to the $85 billion that
UNC spent on energy in 2009-2010 (Strategic Energy and Water Plan, 2010). The payback
periods were determined to range from half of a year to fifty years, depending on the building.
The potential carbon emissions avoided through the production of electricity through these
photovoltaics instead of coal combustion was found to be 440 kilotonnes per year. This
represents a valuable ecological benefit in consideration of the global warming patterns of the
past century and projected models of future warming. Additionally, installing these panels
would bring UNC incrementally closer to achieving Chancellor Moeser’s goal of 80% carbon
emission reductions by 2050. Recent projects implemented by UNC have helped, including
construction of solar thermal arrays on Morrison, implementation of photovoltaic panels on the
Bell Tower parking deck, and installations of energy efficient lighting and occupancy sensor
across campus.
This study represents a preliminary assessment of solar panel suitability on campus.
Further investigations should be undertaken to elaborate upon these findings before the
construction phase. This assessment is limited by a few important assumptions which affect the
final ouput. The potential electrical outputs of the buildings are higher than those produced by
previous solar panel feasibility studies (Chapman Hall Feasibility Study, 2009). These higher
values can be attributed to the large amount of solar panels our analysis placed on within the
rooftops. It was assumed that 25% of each building rooftop would be covered in panels and that
each rooftop was flat. In reality, factors like roof slope and construction impediments such as
eaves, windows, and other rooftop installations would lower both the number of panels and the
potential output of these panels. Additionally, the payback periods of the solar panel
constructions of each building are lower than expected. These payback periods were calculated
using average industry prices that included labor, panel prices, and the inverter. However,
additional construction supports that may be necessary for panel installation, such as those that
would be needed for parking deck installation, are not included. These extra costs tend to drive
up the price of solar panel installations, resulting in final payback periods much longer than our
analysis produced. Furthermore, the Area Solar Radiation tool that we applied to our DEM
assumes a constant clear sky throughout the year. In reality, Chapel Hill receives significant
cloud cover throughout the year, which will lower the calculated potential insolation per unit of
area. Additionally, the spatial resolution of our DEM is relatively course for our analysis. Our 20
ft. cell size resolution distorts the actual rooftop shape and makes the trees larger structures than
they actually are. This distortion of shape in the raster format serves to alter the shading affects
of trees and buildings on rooftops.
In general, it was found that South Campus rooftops are generally better energy
producers when energy output is normalized to rooftop area. North Campus buildings are
affected by higher tree and building density. Regardless of spatial distributions of photovoltaic
arrays, our analysis showed that overall, photovoltaic arrays are a viable option for renewable
energy on campus, and can result in significant monetary and carbon emission savings.
References
Arneman, Daniel. UNC Greenhouse Gas Inventory 2009. Retrieved from
http://www.climate.unc.edu/GHGInventory/reports/GHGInv2009
MBP Construction Engineering, Inc. (2009). Chapman Hall Feasibility Study.
Chapel Hill, NC.
UNC Energy Management. (2010). Strategic Energy and Water Plan. Chapel Hill, NC.
Retrieved from http://save-energy.unc.edu/Portals/2/UNC%20State%20
Energy%20and%20Water%20Report%20FY2009-10.pdf