Master of Environmental Science and Management: Master's Group Project
(2023)

Constructing a Model to Identify Markets for Rooftop Solar on Multifamily Housing

Group Members: Cameron (Cam) Audras, Grace Bianchi, Virginia Pan, Naomi Raal, Julia Bickford

Faculty Advisors: Eric Masanet

Client: Zero Net Energy (ZNE) Capital

Deliverables:

Description

Residential housing’s high energy demand can play a critical role in the transition from fossil fuels to renewable energy. Specifically, multifamily housing provides an opportunity for solar photovoltaic (PV) system adoption. However, landlords are unlikely to install solar PV due to upfront costs. Furthermore, tenants are unlikely to install solar because they often move and the property value increase from solar installation benefits the landlord. To address this, Metropolitan Statistical Areas (MSAs) were identified and ranked across the U.S. for ZNE Capital (the client) to acquire multifamily housing for solar PV installation and rental. Seven criteria were identified to determine favorable MSA markets for rooftop solar PV on multifamily housing: landlord policies, real estate market potential, avoided carbon emissions, electricity generation, solar PV installation profits, climate risk avoidance, and improved health from avoided air pollutants. An investment favorability score was calculated for each MSA based on criteria importance assigned by the model user. Investment favorability scores were calculated for two scenarios, client and equity-centric, to demonstrate the model’s robustness and generalizability. The data was analyzed using RStudio, presenting reproducible code for future solar projects. Results include a ranked list and GIS map of MSAs based on the investment favorability score. In addition, GIS maps of each criterion are included with relative scores of each MSA to illustrate geographic trends. Future studies can utilize the reproducible code to assess investment decisions for solar PV installation on multifamily housing across the US by changing the model’s criteria weights depending on preferences.

Acknowledgements
Bren School: Ranjit Deshmukh, Assistant Professor; Eric Masanet, Professor and Mellichamp Chair in Sustainability Science for Emerging Technologies

ZNE Capital: Owen Barrett, MESM 2012, Earl Mohler

Diane Boss, Ph.D, Dean’s Council, Bren School

John Campanella, President, Bermant Homes

Yardi Systems Group