Student Research Projects

Abstract

Small-scale, residential solar systems have been increasingly recognized as a key sector of future solar capacity growth and carbon emission reduction in cities. This study investigated customer preferences of solar thermal and photovoltaic (PV) systems to facilitate their broader residential penetration. A discrete choice experiment was designed and administered through Amazon Mechanical Turk targeting two testbeds: Boston, Massachusetts and Atlanta, Georgia. Six system features were investigated, including system type, ownership, upfront cost, annual savings, environmental benefits, and neighbor’s choices. The collected data were then analyzed using latent class choice modeling to identify the hidden classes of unique preference characteristics and their spatial distributions. Eight latent classes were identified in each testbed, with only three sharing similar preferences of system features across the two testbeds and none sharing similar socioeconomic characteristics. The testbed-unique grouping of latent classes indicates the importance of understanding preferences case-by-case. Each testbed also has its unique spatial distribution patterns of the latent classes. For instance, early adopters are more evenly distributed in Boston than in Atlanta, indicating the likely broader initial adoption in Boston. Nevertheless, both cities have a substantial number of early adopters residing in lower-property-value regions, revealing a potential to achieve both carbon emission reduction and community renaissance objectives when combining infrastructure renovation projects in these areas with the installation of decentralized energy systems.

Department

Civil and Environmental Engineering

Date of Publication or Presentation

Summer 6-28-2022

Project Type

Graduate Research Project

College or School

CEPS

First Advisor

Weiwei Mo

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