Estimating PV technical potential and financial...

Estimating PV technical potential and financial feasibility for U.S. educational buildings

Nichole HanusGabrielle Wong-Parodi, Inês Azevedo, and Alex Davis

EEDALDistributed Energy Generation

9/13/2017

2

The U.S. relies on fossil fuels.

Coal, 30%

Nuclear, 20%Renewables, 8%

Hydroelectric, 7%

Petroleum, 0.6%

Other, 0.7%

Natural Gas, 34%

Total U.S. Electricity Generation, 2016 [1]

3

Energy services are the largest contributor to greenhouse gases in the U.S.

0

1000

2000

3000

4000

5000

6000

7000

8000

900019

9019

9119

9219

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0420

0520

0620

0720

0820

0920

1020

1120

1220

1320

1420

15

Emis

sion

s (m

illion

met

ric to

ns o

f CO

2eq

uiva

lent

s)

U.S. Greenhouse Gas Emissions by Economic Sector, 1990-2015 [2]

CommercialAgricultureIndustryTransportationElectricity generation

Transportation = 28%

Industry = 22%

Electricity = 30%

4

What role do schools play? [3]

Office20%

Mercantile17%

Food sales & service

11%

Education11%

Health care9%

Public8%

Other8%

Lodging7%

Warehouse & Storage

7%

Religious worship

2%

U.S. Electricity Consumption, 2012 (kWh)

5

What role do schools play? [3]

Office20%

Mercantile17%


11%

Education11%

Health care9%

Public8%

Other8%

Lodging7%

Warehouse & Storage

7%

Religious worship

2%

U.S. Electricity Consumption, 2012 (kWh)

Office19%

Mercantile13%


4%

Education14%

Health care5%

Public8%

Other10%

Lodging7%

Warehouse & Storage

15%

Religious worship

5%

U.S. Floor Space, 2012 (ft2)

6

School budgets could stretch with electricity savings.

• The Department of Energy’s Better Buildings Challenge includes higher education facilities in their goal to reduce building energy consumption by 20% compared to a 2010 baseline [4]

• Annual energy costs: ~ $7.7 billion, or ~225K students’ tuition[5]

Photo 1: U.S. Department of Energy

Photo 2: AASHE

7

What role does solar play?• NREL reports that rooftop PV can deliver 39% of

the total national electric-sector sales [6]

• 1,118 GW of installed capacity• 1,432 TWh of annual energy

8

What role does solar play?• NREL reports that rooftop PV can deliver 39% of

the total national electric-sector sales [6]


• In an economic analysis, NREL finds that building types with the highest breakeven price are small offices, warehouses, and schools [7]

9

What role does solar play?• NREL reports that rooftop PV can deliver 39% of the

total national electric-sector sales [6]


• In an economic analysis, NREL finds that building types with the highest breakeven price are small offices, warehouses, and schools [7]

• Barbose and Darghouth found that installed prices are higher for tax-exempt customer sites than for for-profit commercial sites [8]

• <= 500 kW: Δ $0.3/W• > 500 kW: Δ $1.1/W

10

Research questions1. What is the total potential electricity generation from solar PV on

all U.S. educational buildings for which we have LIDAR data?2. What are the total lifetime costs and benefits – both private and

public – of rooftop solar PV systems installed on all U.S. educational buildings for which we have LIDAR data?

3. How sensitive are the benefit-cost analyses (BCAs) to inputs such as discount factor and the value of net generation (e.g. retail vs. LMP)?

11

Modeloverview

12

Electricity Price

($/kWh)

Electricity Generated by the PV

Panel, when

consuming(kWh/yr)

Electricity Generated by the PV Panel, not consuming(kWh/yr)

Value at which you

sell the electricity

back to the grid

($/kWh)

Installation System Price

($/kW)

Rebates ($/kW)

System Size (kW)

Annual Benefits Upfront Costs

Benefit-Cost Analysis (BCA) at the school level, to be aggregated at county- or state-level

Using the present value of benefit annuities, where i = 7% or 2% and n = 20 years:

School net benefits

𝑃𝑃1 − 1 + 𝑟𝑟 −𝑛𝑛

𝑟𝑟 Equations modified from Azevedo et al. [9]

13

CO2, NOX, PM2.5, and SO2 avoided

damages ($/MWh) at a given seasonal

hour of day

Electricity Generated by the PV

Panel (MWh/yr)

Rebates ($/kW)

System Size (kW)

Annual Benefits Upfront Costs

BCA still at the school level, to be aggregated at county- or state-level

Using the present value of benefit annuities, where i = 7% or 2% and n = 20 years:

Social net benefits

𝑃𝑃1 − 1 + 𝑟𝑟 −𝑛𝑛

𝑟𝑟 Equations modified from Azevedo et al. [9]

14

Building countsIntegrated

Postsecondary Education Data System

(IPEDS) [10]Common Core

of Data (CCD) [11]Private School Universe

Survey (PSS) [12]

Compiler

National Center for Education Statistics

(NCES) from Department of Education

NCES NCES

School Type Private/Public Higher Education K-12 Public K-12 Private

Entries 7,647 102,799 26,983

Year Collected 2015 2015-16 School Year 2011-2012 School Year

Rate of Collection Annually Annually Biennial

After excluding schools with reported latitude and longitude values falling outside of the U.S. boundaries, the combined

dataset includes 134,137 schools.

15

Available roof space• NREL received LIDAR data from the Department

of Homeland Security (DHS) Homeland Security Infrastructure Program (HSIP) [13]

• Covers 128 cities – representing 23% of U.S. buildings and 40% of the U.S. population [13]

• Data gathered between 2006 and 2014 using airplanes and drones [13]

16

LIDAR processed data – NREL

K12 PublicK12 PrivateHigher EducationLIDAR Measurement

17

LIDAR processed data – NREL

K12 PublicK12 PrivateHigher EducationLIDAR Measurement

NREL linked 38,022 schools (28% of all schools)• 41% of higher education• 26% of K12 public• 35% of K12 private

Output: rooftop space (SF)

18

Solar irradiance data & generation estimation

• Calculated output from Typical Meteorological Year (TMY3) insolation data using the method described in Vaishnav et al. [14]

• Assumed that modules are fixed, face south, and that the module tilt angle is equal to the latitude of the location where the module is mounted

PV System Characteristics

Module power density 150 W/m2

Total system losses 14%

Inverter efficiency 96%

DC-to-AC ratio 1.2

TMY3 StationsAssumptions for PV

Performance Simulations

19

Building load profiles• Department of Energy commercial reference buildings [15]

• “Secondary School” type • 210,000 SF• 2 floors• 1,200 students

• 936 Locations – based on TMY3 locations – last updated in 2011• Hourly electricity load profiles (kW) – 8760 entries

0

200

400

600

800

1000

1200

1400

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hou

rly E

lect

ricity

Loa

d (k

W)

Hour of Day

Seattle, WA vs. Houston, TX - May 1

Seattle, WA Houston, TX

20

Installation costs• Use the LBNL Tracking the Sun Database (latest project data: 2015) [8]

• Considering school, government, and non-profit projects • 600 projects out of 800,000 projects• 10 states represented

Mean installed price $ in this dataset:• $4,080/kW• $750,600 overall

21

Electricity Prices - EIA

0

5

10

15

20

25

30

OK TX ID WA VA AR LA WV

NC UT

ND

OR IL NE

SD MO IA WY

NV KY MN IN PA FL GA

CO

OH KS SC MT

TN DE

NM AZ MI

US

MS AL US WI

MD

DC NJ

ME VT NH NY

MA

CA RI

CT

AK HI

Elec

trici

ty P

rice

(cen

ts/k

Wh)

Commercial Retail Electricity Price - 2015

EIA Annual Average for commercial – can use prices by state to calculate the value of the portion displaced (or sold back) [16]

22

PV Rebates - DSIRE• Referencing the DSIRE database: schools, rebates ($/kW) [17]

• Of the states offering such rebates:• Value ranges from $100/kW to $1,200/kW• Capacity limits range from 5 kW to 1 MW

• Currently, we are assuming that net-metering is available for schools in every state and that excess generation is valued at the LMP.

23

Estimating environmental, health & climate change benefits• Based on Siler-Evans et al.’s model in “Regional variations in the health,

environmental, and climate benefits from wind and solar generation” [18,19]

• Azevedo et al. updated model with 2016 emissions for each US fossil fuel power plant > 25 kW [20]

• Estimating Air pollution and Social Impact Using Regression (EASIUR) [21]• Estimate the dispersion of pollutants and the resulting concentrations in all U.S. counties• Use dose-response function to estimate physical impacts• Monetize impacts (e.g. VSL $6-8.6M, market value of lost commodities, etc.)

Photo 3: EASIUR – Marginal Social Costs of Emissions in the United States

24

Quantified costs and benefits𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑠𝑠 = 𝑖𝑖𝑠𝑠 − 𝑔𝑔𝑠𝑠

𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑠𝑠 = 𝑔𝑔𝑠𝑠

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑠𝑠 = �𝑦𝑦=2016

𝑦𝑦=2036��

ℎ=1

ℎ=8760𝑆𝑆𝑠𝑠,ℎ × 𝑝𝑝𝑠𝑠 + �

ℎ=1

ℎ=8760𝑆𝑆𝑠𝑠,ℎ × 𝑆𝑆𝑠𝑠,ℎ ( 1 + )𝑑𝑑 𝑦𝑦−2016

𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑠𝑠 = �𝑦𝑦=2016

𝑦𝑦=2036�

ℎ=1

ℎ=8760𝑆𝑆𝑠𝑠,ℎ + 𝑆𝑆𝑠𝑠,ℎ × )𝑚𝑚(2016 𝑠𝑠,ℎ )/(1 + 𝑑𝑑 𝑦𝑦−2016

25




𝑦𝑦=2036��

ℎ=1


ℎ=1



𝑦𝑦=2036�

ℎ=1


is = total system, s, installation costgs = total system, s, rebate os,h = portion of the output, in kWh, of the electricity generated by a system, s, in hour, h, of a TMYps,y = is the state annual-average commercial retail rate of electricity in year y (set to latest available: 2015)ns,h = output in kWh of the electricity generated by system of a TMY that exceeds consumption and is sold back to the gridls,h = average LMP that prevailed in the state in which the system was installed in hour, h, of 2015 m(2016)s,h = marginal health and environmental damage, expressed in 2016 $ per kWh, avoided by offsetting

a kWh of fossil fuel generation in hour h of year y in the eGrid region where the system s islocated

d = annual discount factor (discount rate set to 7%); therefore, factor is set to (1/1.07)

26




𝑦𝑦=2036��

ℎ=1


ℎ=1



𝑦𝑦=2036�

ℎ=1


is = total system, s, installation costgs = total system, s, rebate os,h = portion of the output, in kWh, of the electricity generated by a system, s, in hour, h, of a TMYps,y = is the state annual-average commercial retail rate of electricity in year y (set to latest available: 2015)ns,h = output in kWh of the electricity generated by system of a TMY that exceeds consumption and is sold back to the gridls,h = average LMP that prevailed in the state in which the system was installed in hour, h, of 2015 m(2016)s,h = marginal health and environmental damage, expressed in 2016 $ per kWh, avoided by offsetting

a kWh of fossil fuel generation in hour h of year y in the eGrid region where the system s islocated

d = annual discount factor (discount rate set to 7%); therefore, factor is set to (1/1.07)

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑐𝑐𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆 = �𝑠𝑠

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑠𝑠 − 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑠𝑠 ∀ 𝑆𝑆𝑔𝑔𝑔𝑔𝑟𝑟𝑆𝑆𝑔𝑔𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆 𝑢𝑢𝑆𝑆𝑖𝑖𝑆𝑆

𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑐𝑐𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆 = �𝑠𝑠

𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑠𝑠 − 𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑠𝑠 ∀ 𝑆𝑆𝑔𝑔𝑔𝑔𝑟𝑟𝑆𝑆𝑔𝑔𝑆𝑆𝑆𝑆𝑖𝑖𝑆𝑆𝑆𝑆 𝑢𝑢𝑆𝑆𝑖𝑖𝑆𝑆

27

Preliminary results: positive social net benefits, negative school net benefits

RQ1. From the schools for which we have LIDAR data, we find a total installed power electricity generation potential:• 1,674 GW• 2,548 TWh of annual energy

28

Preliminary results: positive social net benefits, negative school net benefits

RQ1. From the schools for which we have LIDAR data, we find a total installed power electricity generation potential:• 1,674 GW• 2,548 TWh of annual energy

RQ2. For the LIDAR schools, we arrive at the following net benefits:• School = -3,571,000 million USD• Social = 730,000 million USD

29

Preliminary results: states with most available space don’t always correspond with highest energy potential

30

Preliminary results: school net benefits may vary by retail rates; social net benefits driven by regional energy mix

31

Preliminary results: school net benefits may vary by retail rates; social net benefits driven by regional energy mix

Some regions may have high social benefits, but unfavorable

economics for school

32

Next Steps• Extrapolate LIDAR outputs to buildings outside the 128 cities

• County-level predictors( e.g. Urban/rural distinction, median household income, etc.)• School-level predictors (e.g. school & student population, NCAA affiliation, etc.)

33



• Further sensitivity analyses for the BCAs:• Discount factor• Available rebates• System size• 20-year emissions/damages levels• Avoided electricity charges

34



• Further sensitivity analyses for the BCAs• Discount factor• Available rebates• System size• 20-year emissions/damages levels• Avoided electricity charges

• When calculating the social benefits, what are the differences using the AP2 model and the EASIUR model?

• How much do things change when we consider installing panels on paved unused spaces around campus?

35

Thank you :)

36

AcknowledgementsThis work was completed with support from the Engineering and Public Policy

Department at Carnegie Mellon. This material is also based upon work supported by the National Science Foundation Graduate Research Fellowship Program under

Grant No. DGE1252522 and an international travel allowance through the Graduate Research Opportunities Worldwide (GROW). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not

necessarily reflect the views of the National Science Foundation.

My contact: [email protected]

37

ReferencesPhoto links1. https://betterbuildingssolutioncenter.energy.gov/sites/default/files/attachments/Winter_2016_Progress_Report_0.pdf2. https://stars.aashe.org/institutions/participants-and-reports/3. http://barney.ce.cmu.edu/~jinhyok/easiur/Literature1. Energy Information Agency (EIA). (2017). Electric Power Monthly (US Energy Information Administration, December 23, 2016). Available from: https://www.eia.gov/electricity/data/browser/2. Environmental Protection Agency (EPA). (2017). Greenhouse Gas Inventory Data Explorer. Available from:

https://www3.epa.gov/climatechange/ghgemissions/inventoryexplorer/#allsectors/allgas/econsect/current3. U.S. EIA. (2012). 2012 CBECS Survey Data. Retrieved from https://www.eia.gov/consumption/commercial/data/2012/4. Department of Energy. (2016). Better Buildings Winter 2016 Progress Update. Available from:

https://betterbuildingssolutioncenter.energy.gov/sites/default/files/attachments/Winter_2016_Progress_Report_0.pdf5. NCES. (2016). Fast Facts. Retrieved from https://nces.ed.gov/fastfacts/display.asp?id=766. Gagnon, P., Margolis, R., Melius, J., Phillips, C., & Elmore, R. (2016). Rooftop solar photovoltaic technical potential in the United States: A detailed assessment. National Renewable

Energy Laboratory.7. Davidson, C., Gagnon, P., Denholm, P., & Margolis, R. (2015). Nationwide Analysis of US Commercial Building Solar Photovoltaic (PV) Breakeven Conditions. National Renewable Energy

Laboratory, Golden, CO, USA.8. Barbose, G. L., & Darghouth, N. R. Tracking the Sun IX: The Installed Price of Residential and Non-residential Photovalic Systems in the United States (Washington: US Department of

Energy, 2016). available at emp. lbl. gov/publications/trackin.9. Azevedo, I., Vaishnav, P., and Horner, N. (2016). Location-specific costs and benefits of rooftop solar photovoltaic. iTeam Presentation at Carnegie Mellon University.10. NCES. (2015a). Common Core of Data. Retrieved from https://nces.ed.gov/ccd/pubschuniv.asp11. NCES. (2015b). Integrated Postsecondary Education Data System. Retrieved from https://nces.ed.gov/ipeds/Home/UseTheData12. NCES. (2015c). Private School Universe Survey. Retrieved from https://nces.ed.gov/surveys/pss/tableswhi.asp13. Phillips, C., Melius, J., Gagnon, P., Margolis, R., & Elmore, R. (2016). A Data Mining Approach to Estimating Rooftop Photovoltaic Potential in the U . S ., 1–25.14. Vaishnav, P., Horner, N., & Azevedo, I. L. (2017) Was it worthwhile? Where have the benefits of rooftop solar photovoltaic generation exceeded the cost? Environmental Research Letters.15. DOE. (2017b). Commercial Reference Buildings. Retrieved from https://energy.gov/eere/buildings/commercial-reference-buildings%0A16. OpenEI. (2017). Utility Rate Database. Retrieved from http://en.openei.org/wiki/Utility_Rate_Database17. DSIRE database. Available at: http://ncsolarcen-prod.s3.amazonaws.com/wp-content/uploads/2017/03/Renewable-Portfolio-Standards.pdf18. Siler-Evans, K., Azevedo, I. L., Morgan, M.G, Apt, J. (2013). Regional variations in the health, environmental, and climate benefits from wind and solar generation, Proceedings of the

National Academy of Sciences, 110 (29), 11768-1177319. Siler-Evans. K., Azevedo, I.L., Morgan, M.G., (2012). Marginal emissions factors for the US electricity system. Environmental Science & Technology, 46 (9): 4742–4748.20. Azevedo IL, Horner NC, Siler-Evans K, Vaishnav PT (2017). Electricity Marginal Factor Estimates. Center For Climate and Energy Decision Making. Pittsburgh: Carnegie Mellon University.

http://cedmcenter.org21. Heo, J., Adams, P. J., & Gao, H. O. (2016a). Public Health Costs of Primary PM2.5 and Inorganic PM2.5 Precursor Emissions in the United States. Environmental Science and Technology,

50(11), 6061–6070. https://doi.org/10.1021/acs.est.5b06125

38

Data overview

Building CountsIntegrated Postsecondary Education

Data System (IPEDS)Common Core of Data (CCD)

Private School Universe Survey (PSS)

Solar Irradiance DataNREL TMY3 Data – 936 locations

Building Load ProfileDOE – 936 locations

Cost & RebatesLBNL Tracking the Sun

DSIRE

Electricity PricesEIA 2015 Avg. for Commercial

Roof DataNREL LIDAR Data

Google Earth

Quantified DamagesEASIUR Model

AP2 Model

39

LIDAR method• NREL received LIDAR data from the Department

of Homeland Security (DHS) Homeland Security Infrastructure Program (HSIP) [18]

• Covers 128 cities – representing 23% of U.S. buildings and 40% of the U.S. population [18]

• Data gathered between 2006 and 2014 using airplanes and drones [18]

• LIDAR uses light in the form of a pulsed laser to measure variable distances to earth [19]

• NREL uses LIDAR data in combination with GIS methods to characterize suitable rooftop space [11]

40

Net Metering - DSIRE• Net metering agreements vary widely across the U.S. [23]

• Could assume two scenarios for the electricity sold back to the grid:• Retail prices• Local marginal price (LMP)

Photo 13: DSIRE

41

Installation costs and rebates• Use the LBNL Tracking the Sun Database (latest project data: 2015) [13]

• Considering school, government, and non-profit projects • 600 projects out of 800,000 projects• 10 states represented

Mean installed price $ in this dataset:• $4,080/kW• $750,600 overall

Mean rebate or grant $ in this dataset:• $184/kW• $8,492 overall

Estimating PV technical potential and financial...

Documents

Transcript of Estimating PV technical potential and financial...