Distributed Solar Adoption in Orlando: A Household-Level Model for Distribution Resource Planning

Technical Report · Tue Jan 12 04:00:00 EST 2021

DOI:https://doi.org/10.2172/1762446· OSTI ID:1762446

Koebrich, Samuel ^[1]; Sigrin, Benjamin ^[1]; Spencer, Robert ^[1]; Schwabe, Paul ^[1]; Haase, Scott ^[1]; Choi, Sam ^[2]; Kramer, Justin ^[2]

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1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
2. Orlando Utilities Commission, FL (United States)

Potential for rooftop solar in Florida is massive (47% of retail sales, 3rd overall nationally), yet adoption lags (12th nationally). A 2018 Florida Public Service Commission ruling authorizing solar third-party ownership (leasing) has substantially increased attention on distributed solar in the state. The city of Orlando has committed to a 100% clean-energy target by 2050 and deployment of solar and storage are expected to contribute significantly to reaching the goal. Deployment of customer-adopted solar, unlike utility-procured solar, is uncertain, but known to be spatially correlated with demographic factors and existing adoption. We develop a new method to adapt NREL's dGen model in order to represent building-level agents in adoption forecasts for the Orlando Utility Commission (OUC) service territory. Using the agent-based model we develop projections of solar adoption, subject to scenarios varying future solar costs and valuation, and aggregate adoption predictions by OUC distribution feeder. We find substantial spatial heterogeneity in the projected level of adoption by OUC distribution feeder. For instance, 25% of all projected adoption through 2050 would be concentrated on just 5% of feeders and 88% of projected adoption on 50% of feeders. Because of the uncertainty in adoption, bottoms-up solar adoption forecasting methods at the household-level are integral to long-term resource planning by anticipating system needs as customers increasingly adopt distributed solar, storage, electric vehicles, and other distributed energy resources.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE; Orlando Utilities Commission, FL (United States)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1762446
• Report Number(s): NREL/PR--6A20-77308; MainId:26254; UUID:a68cb842-26d9-4c4f-941e-4974c7349fad; MainAdminID:19154
• Country of Publication: United States
• Language: English

Related Subjects

14 SOLAR ENERGY
24 POWER TRANSMISSION AND DISTRIBUTION
Florida
Orlando Utility Commission
agent based modeling
customer adoption modeling
distributed solar
distribution resource planning
forecasting
integrated resource planning
machine learning