Title

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.

Faculty Mentor(s)

Robert Hickey, Charles Wassell, and Hongtao Dang

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/

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May 16th, 12:00 PM May 22nd, 12:00 PM

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