Evaluating Determinants of Residential Solar Photovoltaic (PV) Uptake in Washington State: A Spatial-Temporal analysis of 2000
Document Type
Poster
Campus where you would like to present
Ellensburg
Event Website
https://digitalcommons.cwu.edu/source
Start Date
16-5-2021
End Date
22-5-2021
Keywords
Climate Change, Sustainability, Solar Power
Abstract
The Earth is experiencing the effects of climactic warming as a result of greenhouse gas emissions. One way to address this problem is to replace existing generation capacity with clean sourced energy such as photovoltaic (PV) solar. Washington State’s Clean Energy Transformation Act, amongst other state and federal policies encouraging solar, make WA a candidate for research on local determinants and barriers to residential uptake. In this project, residential solar uptake is mapped by county (2000-2019) and census tract (2017-2019) in cumulative and non-cumulative manners to identify trends over time and space. Installations and capacity were normalized by households to account for the skewed population distributions. These were run against demographic, electricity price, and solar potential variables in uni-and multi-variate regression models in an attempt to explain the distribution of residential solar installations in WA. The tract-level results were inconclusive, perhaps because the determinants operate at larger scales. At the county level, the models are robust and parallel existing literature. For the un-normalized data, the variables accounted for 95% of the variance in the dataset, however, we think this is largely explained by the population distribution in WA. Once normalized, the following variables accounted for only 45% of the variance: college attainment, a younger population base (20-55 year-olds), household income, and households. We posit that there are other variables at play which could include local utility policies; the ease of obtaining loans, permits, and installation; peer influences; or local programs that encourage residents to invest in clean energy.
Recommended Citation
Valko, Caleb, "Evaluating Determinants of Residential Solar Photovoltaic (PV) Uptake in Washington State: A Spatial-Temporal analysis of 2000" (2021). Symposium Of University Research and Creative Expression (SOURCE). 42.
https://digitalcommons.cwu.edu/source/2021/COTS/42
Department/Program
Cultural and Environmental Resource Management
Additional Mentoring Department
Geography
Additional Mentoring Department
Economics
Additional Mentoring Department
Engineering Technologies, Safety, and Construction
Additional Mentoring Department
https://cwu.studentopportunitycenter.com/evaluating-determinants-of-residential-solar-photovoltaic-pv-uptake-in-washington-state-a-spatial-temporal-analysis-of-2000/
Evaluating Determinants of Residential Solar Photovoltaic (PV) Uptake in Washington State: A Spatial-Temporal analysis of 2000
Ellensburg
The Earth is experiencing the effects of climactic warming as a result of greenhouse gas emissions. One way to address this problem is to replace existing generation capacity with clean sourced energy such as photovoltaic (PV) solar. Washington State’s Clean Energy Transformation Act, amongst other state and federal policies encouraging solar, make WA a candidate for research on local determinants and barriers to residential uptake. In this project, residential solar uptake is mapped by county (2000-2019) and census tract (2017-2019) in cumulative and non-cumulative manners to identify trends over time and space. Installations and capacity were normalized by households to account for the skewed population distributions. These were run against demographic, electricity price, and solar potential variables in uni-and multi-variate regression models in an attempt to explain the distribution of residential solar installations in WA. The tract-level results were inconclusive, perhaps because the determinants operate at larger scales. At the county level, the models are robust and parallel existing literature. For the un-normalized data, the variables accounted for 95% of the variance in the dataset, however, we think this is largely explained by the population distribution in WA. Once normalized, the following variables accounted for only 45% of the variance: college attainment, a younger population base (20-55 year-olds), household income, and households. We posit that there are other variables at play which could include local utility policies; the ease of obtaining loans, permits, and installation; peer influences; or local programs that encourage residents to invest in clean energy.
https://digitalcommons.cwu.edu/source/2021/COTS/42
Faculty Mentor(s)
Robert Hickey, Charles Wassell, and Hongtao Dang