Adoption of Diffused Renewable Energy Technologies: Patterns and Drivers of Residential Photovoltaic (PV) Systems in Connecticut, 2005-2013

Growing concern about global climate change and energy security are prompting reconsideration of how energy—particularly electricity—is generated, transmitted, and consumed in the United States and across the globe. While an increasing amount of households are adopting solar power across the developed world, the spatial and socioeconomic factors that shape whether or not people adopt this technology is under-theorized (especially with regard to spatial drivers), and not well researched from an empirical perspective. In my dissertation, I present a conceptual model to describe and understand the socioeconomic and spatial factors affecting the diffusion of PV systems. I build my model on the socio-technical tradition. Further, I present two empirical studies where I combine statistical and mapping techniques aimed at finding the spatial patterns and the underlying drivers influencing the adoption of PV systems in Connecticut since 2005. I develop an innovative spatiotemporal band to control for spatial peer effects, while using several socioeconomic and spatial variables to control for other factors. Contrary to previous literature, I find that medium-sized centers represent the source of the diffusion, rather than larger, more populous towns. Further, I find that spatial peer effects positively affect the adoption process, while the lack of more refined and spatially conscious policies tend to make adoption more difficult in densely populated areas. However, spatial peer effects tend to decrease in magnitude as time and space increase. Finally, I find that current policies, which do not taking in to account the differences in the socioeconomic and built environment among towns in Connecticut, fail to reach potential adopters residing in multi-family buildings or in renter-occupied houses