文献详情
Using willingness to pay to forecast the adoption of solar photovoltaics: A "parameterization plus calibration" approach
文献类型：期刊
通讯作者：Dong, CG (reprint author), Renmin Univ China, Sch Publ Adm & Policy, 59 Zhongguancun St,Qiushi Bldg 411, Beijing 100872, Peoples R China.
期刊名称：ENERGY POLICY影响因子和分区
年：2019
卷：129
页码：100-110
ISSN：0301-4215
关键词：Solar photovoltaics; Willingness to pay; Adoption forecasting; Parameterization; Calibration
所属部门：公共管理学院
摘要：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 peoples 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 a ...More
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 peoples 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. ...Hide

DOI：10.1016/j.enpol.2019.02.017
百度学术：Using willingness to pay to forecast the adoption of solar photovoltaics: A "parameterization plus calibration" approach
语言：外文
被引频次：1
基金：United States Department of Energy Solar Energy Technology Office SEEDS Program (Solar Energy Evolution and Diffusion Studies) [DE-FOA-0000740]
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