Carolyn Davidson
National Renewable Energy Laboratory
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Featured researches published by Carolyn Davidson.
Archive | 2015
David Feldman; Galen Barbose; Robert Margolis; Mark Bolinger; Donald Chung; Ran Fu; Joachim Seel; Carolyn Davidson; Naim Darghouth; Ryan Wiser
This presentation, based on research at Lawrence Berkeley National Laboratory and the National Renewable Energy Laboratory, provides a high-level overview of historical, recent, and projected near-term PV pricing trends in the United States focusing on the installed price of PV systems. It also attempts to provide clarity surrounding the wide variety of potentially conflicting data available about PV system prices. This PowerPoint is the third edition from this series.
Archive | 2015
Donald Chung; Carolyn Davidson; Ran Fu; Kristen Ardani; Robert Margolis
The price of photovoltaic (PV) systems in the United States (i.e., the cost to the system owner) has continued to decline across all major market sectors. This report provides a Q1 2015 update regarding the prices of residential, commercial, and utility scale PV systems, based on an objective methodology that closely approximates the book value of a PV system. Several cases are benchmarked to represent common variations in business models, labor rates, and system architecture choice. We estimate a weighted-average cash purchase price of
Environmental Research Letters | 2015
Carolyn Davidson; Daniel Steinberg; Robert Margolis
3.09/W for residential scale rooftop systems,
Environmental Research Letters | 2014
Carolyn Davidson; Easan Drury; Anthony Lopez; Ryan Elmore; Robert Margolis
2.15/W for commercial scale rooftop systems,
Archive | 2014
Carolyn Davidson; Ted James; Robert Margolis; Ran Fu; David Feldman
1.77/W for utility scale systems with fixed mounting structures, and
photovoltaic specialists conference | 2013
Kristen Ardani; Daniel Seif; Carolyn Davidson; Jesse Morris; Sarah Truitt; Roy Torbert; Robert Margolis
1.91/W for utility scale systems using single-axis trackers. All systems are modeled assuming standard-efficiency, polycrystalline-silicon PV modules, and further assume installation within the United States.
Renewable Energy Focus | 2014
David Feldman; Galen Barbose; Robert Margolis; Ted James; Samantha Weaver; Naim Darghouth; Ran Fu; Carolyn Davidson; Sam Booth; Ryan Wiser
Over the past several years, third-party-ownership (TPO) structures for residential photovoltaic (PV) systems have become the predominant ownership model in the US residential market. Under a TPO contract, the PV system host typically makes payments to the third-party owner of the system. Anecdotal evidence suggests that the total TPO contract payments made by the customer can differ significantly from payments in which the system host directly purchases the system. Furthermore, payments can vary depending on TPO contract structure. To date, a paucity of data on TPO contracts has precluded studies evaluating trends in TPO contract cost. This study relies on a sample of 1113 contracts for residential PV systems installed in 2010–2012 under the California Solar Initiative to evaluate how the timing of payments under a TPO contract impacts the ultimate cost of the system to the customer. Furthermore, we evaluate how the total cost of TPO systems to customers has changed through time, and the degree to which contract costs have tracked trends in the installed costs of a PV system. We find that the structure of the contract and the timing of the payments have financial implications for the customer: (1) power-purchase contracts, on average, cost more than leases, (2) no-money-down contracts are more costly than prepaid contracts, assuming a customer’s discount rate is lower than 17% and (3) contracts that include escalator clauses cost more, for both power-purchase agreements and leases, at most plausible discount rates. In addition, all contract costs exhibit a wide range, and do not parallel trends in installed costs over time.
Renewable Energy Focus | 2014
Barry Friedman; Kristen Ardani; David Feldman; Daniel Seif; Carolyn Davidson; Jesse Morris; Sarah Truitt; Roy Torbert; Robert Margolis
This study combines address-level residential photovoltaic (PV) adoption trends in California with several types of geospatial information—population demographics, housing characteristics, foreclosure rates, solar irradiance, vehicle ownership preferences, and others—to identify which subsets of geospatial information are the best predictors of historical PV adoption. Number of rooms, heating source and house age were key variables that had not been previously explored in the literature, but are consistent with the expected profile of a PV adopter. The strong relationship provided by foreclosure indicators and mortgage status have less of an intuitive connection to PV adoption, but may be highly correlated with characteristics inherent in PV adopters. Next, we explore how these predictive factors and model performance varies between different Investor Owned Utility (IOU) regions in California, and at different spatial scales. Results suggest that models trained with small subsets of geospatial information (five to eight variables) may provide similar explanatory power as models using hundreds of geospatial variables. Further, the predictive performance of models generally decreases at higher resolution, i.e., below ZIP code level since several geospatial variables with coarse native resolution become less useful for representing high resolution variations in PV adoption trends. However, for California we find that model performance improves if parameters are trained at the regional IOU level rather than the state-wide level. We also find that models trained within one IOU region are generally representative for other IOU regions in CA, suggesting that a model trained with data from one state may be applicable in another state.
Energy Economics | 2013
Jeffrey Logan; Anthony Lopez; Trieu Mai; Carolyn Davidson; Morgan Bazilian; D. J. Arent
The price of photovoltaic (PV) systems in the United States (i.e., the cost to the system owner) has dropped precipitously in recent years, led by substantial reductions in global PV module prices. This report provides a Q4 2013 update for residential PV systems, based on an objective methodology that closely approximates the book value of a PV system. Several cases are benchmarked to represent common variation in business models, labor rates, and module choice. We estimate a weighted-average cash purchase price of
Archive | 2014
David Feldman; Galen Barbose; Ted James; Samantha Weaver; Ran Fu; Carolyn Davidson
3.29/W for modeled standard-efficiency, polycrystalline-silicon residential PV systems installed in the United States. This is a 46% decline from the 2013-dollar-adjusted price reported in the Q4 2010 benchmark report. In addition, this report frames the cash purchase price in the context of key price metrics relevant to the continually evolving landscape of third-party-owned PV systems by benchmarking the minimum sustainable lease price and the fair market value of residential PV systems.