Carnegie Mellon University
Evaluating Rooftop Solar Parity for Commercial Customers
Shelly Hagerman, Paulina Jaramillo, M. Granger MorganCarnegie Mellon University
October 26, 20152015 USAEE Pittsburgh
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Previous Work
• Socket parity analysis– Residential Customers– Over 1,000 locations
No Subsidies Federal ITC Federal ITC + State
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Are Commercial Customers at Parity?• Different rate tariff structures• Economies of scale in solar PV pricing• Ability to finance
• Potential Adjustments– Load shifting– Change in tariff
Source: NJR Clean Energy Ventures
Source: Titan Solar Construction
Source: Public Power Solutions
Source: SbS Services
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Timeline and Framework
Initial Case Study
Jun-Sep
ExpansionOct-Nov
Final Report
Nov-Dec
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Constructing an Initial Case Study
• Raleigh, North Carolina– Rapid commercial growth due to 35% state tax
credit (Exp. 12/31/15)– Potential access to measured load and solar PV
data• Initial data inputs– DOE commercial reference building load profiles– Solar output model used in previous research– Reference tariffs
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DOE Commercial Reference Building Profiles
• Hourly simulated data– Uses TMY data (same
weather data as solar output model)
• 16 building types (2,500 sf – 500,000 sf)• 16 climate zones
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Primary Components of Commercial Rate Tariffs
• Customer Charge– Fixed, part of
monthly minimum bill
• Demand Charges– Capacity based
($/kW)• Flat, tiered,
seasonal
• Energy Charges– Flat, tiered, hours of
use ($/kWh)7
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PRELIMINARY RESULTS
Initial Case Study
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Commercial Customer Bills – Breakdown of ChargesLarger Proportion from Demand Charges for Larger Customers and those on Time-of-Use Rates
Energy Charges
Customer Charge Demand Charges
Energy Charges
Customer Charge
Demand Charges
Energy Charges
Customer Charge
Energy Charges
Customer Charge
Demand Charges
Energy Charges
Customer Charge
Demand ChargesEnergy
Charges
Customer Charge
Defa
ult
Tim
e-o
f-U
se
Small Medium Large
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Breakdown of Savings: Demand vs. Energy
System Size: 10kWInstalled Cost: $3.23/W
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Demand Charges May Prohibit Economic Viability
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Breakeven Costs between $1.50 and $2.10/W
• Above SunShot Initiative’s 2020 goal (positive NPV)
• Supermarket best, hospital worst
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Preliminary Findings: Initial Case Study
• Small general service with time-of-use potentially most profitable
• NPV improves when peak demand coincident with solar
• Positive NPV by 2020 if SunShot goal is met
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PRELIMINARY RESULTS
Expansion
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Expansion - Measured Data• Load data– Currently: NC commercial load profiles (15-minute
resolution)– Future: EPRI CA Office Building (1-minute resolution)
• Solar data– Currently: • 1MW PV Plant in East, TN (1-minute resolution)
– Future: • 1MW PV Plant in NC• 200kW PV Plant in CA (from same office building as load
data) 15
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Hourly Resolution Solar Data Can Both Overestimate and Underestimate Demand Savings in any Given Month
1-hr resolution solar data overestimated demand savings by an annual percentage difference of 28%, compared actual to 15-min averages
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Next Steps
• Research questions:– Does rate structure matter?– Do hourly simulated data adequately estimate demand
charges?– To what extent do building load profiles matter?– Can storage or demand-side management improve economics?
• Implications:– Provide framework for aggregating raw data to extend analysis
to different locations– Contribute to discussion of financial viability of PV and rate
reform
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Acknowledgements
• Support for this work has come from NSF through the Center for Climate and Energy Decision Making under cooperative agreement SES-0345798, Carnegie Mellon Electricity Industry Center, and Electric Power Research Institute.
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Thank you!
Questions?
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Solar Data Resolution Can Affect Demand Savings
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Carnegie Mellon University
Solar Data Resolution Can Affect Demand Savings
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