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Using willingness to pay to forecast the adoption of solar photovoltaics: A “parameterization + calibration” approach

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  • Dong, Changgui
  • Sigrin, Benjamin

Abstract

Distributed energy resources, such as rooftop solar photovoltaics (PV), are likely to comprise a substantial fraction of new generation capacity in the United States. However, forecasting technology adoption based on people's willingness to pay (WTP) faces two major challenges: the stated-intention and omitted-variable biases. Previous solar adoption literature has neglected to address these two biases altogether. Here, we adopt a “parameterization + calibration” approach to address both biases and estimate customers’ WTP for PV. After collecting survey data on respondents’ WTP for adopting PV, we characterize its empirical cumulative density function using a gamma distribution. We further calibrate the gamma distribution parameters using a national distributed PV adoption simulation model, finding the parameters that produce the best fit between simulated and historic solar adoption. We then show that the calibrated gamma distribution improves the raw WTP data after correcting for the two biases. Finally, we use our optimally-calibrated WTP to forecast market demand for residential PV at the county-level of the United States in 2020. Improving estimates of customer willingness to pay has significant implications for policy directly, e.g. estimating the effect of a proposed policy on technology adoption, and other regulatory processes that use forecasting, e.g. integrated resource planning.

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  • Dong, Changgui & Sigrin, Benjamin, 2019. "Using willingness to pay to forecast the adoption of solar photovoltaics: A “parameterization + calibration” approach," Energy Policy, Elsevier, vol. 129(C), pages 100-110.
    • Handle: RePEc:eee:enepol:v:129:y:2019:i:c:p:100-110
    DOI: 10.1016/j.enpol.2019.02.017
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    6. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2021. "Diffusion forecast for grid-tied rooftop solar photovoltaic technology under store-on grid scheme model in Sub-Saharan Africa: Government role assessment," Renewable Energy, Elsevier, vol. 180(C), pages 516-535.
    7. Motz, Alessandra, 2021. "Consumer acceptance of the energy transition in Switzerland: The role of attitudes explained through a hybrid discrete choice model," Energy Policy, Elsevier, vol. 151(C).
    8. Sommerfeldt, Nelson & Pearce, Joshua M., 2023. "Can grid-tied solar photovoltaics lead to residential heating electrification? A techno-economic case study in the midwestern U.S," Applied Energy, Elsevier, vol. 336(C).
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