The Department of Energy has given a roughly $500,000 grant to a UT research project that hopes to shed light on solar and non-solar energy use in Texas, with particular attention to what gets consumers amped up.
Texas is one of the best areas in the U.S. to harvest solar power, according to Rai. He said the project will examine what obstacles prevent its use, particularly in residential areas. Rai also said he hopes the data will result in the development of more solar technologies, such as systems to power homes and electric vehicles.
“Through a robust research design combining behavioral economics, diffusion of innovations and advanced data analytics, this project seeks to support the overarching objective of making renewable energy, and solar in particular, more affordable and widespread,” Rai said.
Many solar power systems run rebate programs, according to Eric Bickel, an associate professor of mechanical engineering at UT who is assisting with the project. Because solar power is now much cheaper than it was 40 or 50 years ago, when it was first invented, this project will investigate how to make solar energy more widespread. Similar grants were also awarded to MIT, the University of North Carolina at Charlotte and Yale University as part of the department’s SunShot Initiative.
Ben Sigrin, a public affairs and energy and earth resources graduate student working on the project, said the project comes at a time when solar energy is at a crossroads.
“The prices have fallen so quickly over the last few years that we’re now at a point where solar could actually become mainstream,” Sigrin said. “Our research helps understand why consumers adopt solar and ways to accelerate that adoption process.”
Scott Robinson, public affairs and energy and earth resources graduate student, is designing a “computer simulation of the residential solar market in Austin” with hopes of simulating consumer behavior as a part of the research project.
“I am using agent-based modeling to solve this problem,” Robinson said. “Instead of using an algorithm to describe the process as a whole, I model the behavior of individuals, and allow them to interact within their geographic environment.”
This project has been a dream come true from a student’s perspective, Robinson said.
“To be honest, this project is the most interesting problem I have ever tried to solve,” Robinson said. “It has made me search out an entire new skill set in an applied environment. In other words, this is what learning should be.”