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.

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).

Fetzer Gym

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 MW-

hr), 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 g-

CO2/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 fromhttp :// www . climate . unc . edu / GHGInventory / reports / GHGInv 2009

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