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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Solar Data Resolution Can Affect Demand Savings

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