Final Report: Towards an Emergent Model of Technology Adoption for Accelerating the Diffusion of Residential Solar PV
- Univ. of Texas, Austin, TX (United States)
This project sought to enable electric utilities in Texas to accelerate diffusion of residential solar photovoltaic (PV) by systematically identifying and targeting existing barriers to PV adoption. A core goal of the project was to develop an integrated research framework that combines survey research, econometric modeling, financial modeling, and implementation and evaluation of pilot projects to study the PV diffusion system. This project considered PV diffusion as an emergent system, with attention to the interactions between the constituent parts of the PV socio-technical system including: economics of individual decision-making; peer and social influences; behavioral responses; and information and transaction costs. We also conducted two pilot projects, which have yielded new insights into behavioral and informational aspects of PV adoption. Finally, this project has produced robust and generalizable results that will provide deeper insights into the technology-diffusion process that will be applicable for the design of utility programs for other technologies such as home-energy management systems and plug-in electric vehicles. When we started this project in 2013 there was little systematic research on characterizing the decision-making process of households interested in adopting PV. This project was designed to fill that research gap by analyzing the PV adoption process from the consumers' decision-making perspective and with the objective to systematically identifying and addressing the barriers that consumers face in the adoption of PV. The two key components of that decision-making process are consumers' evaluation of: (i) uncertainties and non-monetary costs associated with the technology and (ii) the direct monetary cost-benefit. This project used an integrated approach to study both the non-monetary and the monetary components of the consumer decision-making process.
- Research Organization:
- Univ. of Texas, Austin, TX (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- DOE Contract Number:
- EE0006129
- OSTI ID:
- 1332932
- Report Number(s):
- Final Report: DOE-UTAustin-EE0006129-1
- Resource Relation:
- Related Information: 1. Rai, V. and Beck. A. L. (2016) Serious games in breaking informational barriers in solar energy. Under Review. Preprint available at: http://ssrn.com/abstract=28168522. Rai, V., & Henry, A. D. (2016). Agent-based modelling of consumer energy choices. Nature Climate Change, DOI: 10.1038/NCLIMATE2967.3. Rai, V., & Beck, A. L. (2015). Public perceptions and information gaps in solar energy in Texas. Environmental Research Letters, 10(7), 074011.4. Robinson, S. A., & Rai, V. (2015). Determinants of spatio-temporal patterns of energy technology adoption: An agent-based modeling approach. Applied Energy, 151, 273-284.5. Rai, V., & Robinson, S. A. (2015). Agent-based modeling of energy technology adoption: empirical integration of social, behavioral, economic, and environmental factors. Environmental Modelling & Software, 70, 163-177.
- Country of Publication:
- United States
- Language:
- English
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