skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: What Factors Affect the Prices of Low-Priced U.S. Solar PV Systems?

Abstract

The price of solar PV systems has declined rapidly, yet there are some much lower-priced systems than others. This study explores the factors leading some systems to be so much lower priced than others. Using a data set of 42,611 residential-scale PV systems installed in the U.S. in 2013, we use quantile regressions to estimate the importance of factors affecting the installed prices for low-priced (LP) systems (those at the 10th percentile) in comparison to median-priced systems. We find that the value of solar to consumers–a variable that accounts for subsidies, electric rates, and PV generation levels–is associated with lower prices for LP systems but higher prices for median priced systems. Conversely, systems installed in new home construction are associated with lower prices at the median but higher prices for LP. Other variables have larger cost-reducing effects on LP than on median priced systems: systems installed in Arizona and Florida, as well as commercial and thin film systems. In contrast, the following have a smaller effect on prices for LP systems than median priced systems: tracking systems, self-installations, systems installed in Massachusetts, the system size, and installer experience. These results highlight the complex factors at play that lead to LPmore » systems and shed light into how such LP systems can come about.« less

Authors:
 [1];  [2];  [3];  [3];  [3];  [4];  [5]
  1. Univ. of Wisconsin, Madison, WI (United States); Mercator Research Inst. on Global Commons and Climate Change, Berlin (Germany)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  4. Yale Univ., New Haven, CT (United States)
  5. Univ. of Texas, Austin, TX (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1378573
Report Number(s):
LBNL-1006193
ir:1006193
DOE Contract Number:
AC02-05CH11231; AC36-08GO28308
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY

Citation Formats

Nemet, Gregory F., O'Shaughnessy, Eric, Wiser, Ryan, Darghouth, Naïm R., Barbose, Galen, Gillingham, Ken, and Rai, Varun. What Factors Affect the Prices of Low-Priced U.S. Solar PV Systems?. United States: N. p., 2016. Web. doi:10.2172/1378573.
Nemet, Gregory F., O'Shaughnessy, Eric, Wiser, Ryan, Darghouth, Naïm R., Barbose, Galen, Gillingham, Ken, & Rai, Varun. What Factors Affect the Prices of Low-Priced U.S. Solar PV Systems?. United States. doi:10.2172/1378573.
Nemet, Gregory F., O'Shaughnessy, Eric, Wiser, Ryan, Darghouth, Naïm R., Barbose, Galen, Gillingham, Ken, and Rai, Varun. 2016. "What Factors Affect the Prices of Low-Priced U.S. Solar PV Systems?". United States. doi:10.2172/1378573. https://www.osti.gov/servlets/purl/1378573.
@article{osti_1378573,
title = {What Factors Affect the Prices of Low-Priced U.S. Solar PV Systems?},
author = {Nemet, Gregory F. and O'Shaughnessy, Eric and Wiser, Ryan and Darghouth, Naïm R. and Barbose, Galen and Gillingham, Ken and Rai, Varun},
abstractNote = {The price of solar PV systems has declined rapidly, yet there are some much lower-priced systems than others. This study explores the factors leading some systems to be so much lower priced than others. Using a data set of 42,611 residential-scale PV systems installed in the U.S. in 2013, we use quantile regressions to estimate the importance of factors affecting the installed prices for low-priced (LP) systems (those at the 10th percentile) in comparison to median-priced systems. We find that the value of solar to consumers–a variable that accounts for subsidies, electric rates, and PV generation levels–is associated with lower prices for LP systems but higher prices for median priced systems. Conversely, systems installed in new home construction are associated with lower prices at the median but higher prices for LP. Other variables have larger cost-reducing effects on LP than on median priced systems: systems installed in Arizona and Florida, as well as commercial and thin film systems. In contrast, the following have a smaller effect on prices for LP systems than median priced systems: tracking systems, self-installations, systems installed in Massachusetts, the system size, and installer experience. These results highlight the complex factors at play that lead to LP systems and shed light into how such LP systems can come about.},
doi = {10.2172/1378573},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 8
}

Technical Report:

Save / Share:
  • The price of solar PV systems has declined rapidly, yet there are some much lower-priced systems than others. This study explores the factors that determine prices in these low-priced (LP) systems. Using a data set of 42,611 residential-scale PV systems installed in the U.S. in 2013, we use quantile regressions to estimate the importance of factors affecting the installed prices for LP systems (those at the 10th percentile) in comparison to median-priced systems. We find that the value of solar to consumers-a variable that accounts for subsidies, electric rates, and PV generation levels-is associated with lower prices for LP systemsmore » but higher prices for median priced systems. Conversely, systems installed in new home construction are associated with lower prices at the median but higher prices for LP. Other variables have larger price-reducing effects on LP than on median priced systems: systems installed in Arizona and Florida, as well as commercial and thin film systems. In contrast, the following have a smaller effect on prices for LP systems than median priced systems: tracking systems, self-installations, systems installed in Massachusetts, the system size, and installer experience. Furthermore, these results highlight the complex factors at play that lead to LP systems and shed light into how such LP systems can come about.« less
  • Despite impressive recent cost reductions, there is wide dispersion in the prices of installed solar photovoltaic (PV) systems. We identify the most important factors that make a system likely to be low priced (LP). Our sample consists of detailed characteristics for 42,611 small-scale (< 15 kW) PV systems installed in 15 U.S. states during 2013. Using four definitions of LP systems, we compare LP and non-LP systems and find statistically significant differences in nearly all factors explored, including competition, installer scale, markets, demographics, ownership, policy, and system components. Logit and probit model results robustly indicate that LP systems are associatedmore » with markets with few active installers; experienced installers; customer ownership; large systems; retrofits; and thin-film, low-efficiency, and Chinese modules. We also find significant differences across states, with LP systems much more likely to occur in some than in others. Our focus on the left tail of the price distribution provides implications for policy that are distinct from recent studies of mean prices. While those studies find that PV subsidies increase mean prices, we find that subsidies also generate LP systems. PV subsidies appear to simultaneously shift and broaden the price distribution. Much of this broadening occurs in a particular location, northern California, which is worthy of further investigation with new data.« less
  • Business process or “soft” costs account for well over 50% of the installed price of residential photovoltaic (PV) systems in the United States, so understanding these costs is crucial for identifying PV cost-reduction opportunities. Among these costs are those imposed by city-level permitting processes, which may add both expense and time to the PV development process. Building on previous research, this study evaluates the effect of city-level permitting processes on the installed price of residential PV systems and on the time required to develop and install those systems. The study uses a unique dataset from the U.S. Department of Energy’smore » Rooftop Solar Challenge Program, which includes city-level permitting process “scores,” plus data from the California Solar Initiative and the U.S. Census. Econometric methods are used to quantify the price and development-time effects of city-level permitting processes on more than 3,000 PV installations across 44 California cities in 2011. Results indicate that city-level permitting processes have a substantial and statistically significant effect on average installation prices and project development times. The results suggest that cities with the most favorable (i.e., highest-scoring) permitting practices can reduce average residential PV prices by $0.27–$0.77/W (4%–12% of median PV prices in California) compared with cities with the most onerous (i.e., lowest-scoring) permitting practices, depending on the regression model used. Though the empirical models for development times are less robust, results suggest that the most streamlined permitting practices may shorten development times by around 24 days on average (25% of the median development time). These findings illustrate the potential price and development-time benefits of streamlining local permitting procedures for PV systems.« less
  • Now we are abruptly against an important policy question: Do we have two laudable goals which are fundamentally inconsistent with one another. Is it possible to blunt the impact of rapidly rising energy prices on some of the customers without subverting the goals of prudent use in the long term. To answer this question we must step back and look at fundamental empirical evidence of the relationship between prices and the use of electricity; that is the subject of the first section. Second, we look especially at the evidence of differential impact by level of use or level of income.more » Finally, we will review in particular an electricity lifeline rate that was adopted in Los Angeles and evaluate it against these two social objectives of efficiency and improved well-being of lower income individuals. Without intending to give away the plot, I will tell you at the outset that there will be some pleasant surprises. Our analysis indicates that, at least under some circumstances, public policies can be designed to help the poor through the pricing mechanism without destroying the efficiency gains that are generally found with market prices that reflect the full costs of production and supply.« less
  • This Appendix to MITRE/METREK Report MTR-7485 (''System Descriptions and Engineering Costs for Solar-Related Technologies, Volume I'') presents the findings of a limited study of experience curve and cost trend histories within a wide range of commodities relevant to projected solar energy system concepts. Two forms of data presentation are used: (1) experience curves derived from production volume and unit cost inputs and (2) cost trend curves where data on accumulated production volumes are not readily available. Although many years of historical data have been assembled, it has seldom been possible to acquire those relating to the onset of production. However,more » in the context of the objective of this Appendix, cost tends in relatively recent--say, ten to twenty--years are the more important consideration. Bearing in mind that projected solar energy systems will comprise elements of conventional plant equipment, materials, construction, etc., as well as those unique to such systems, experience curve and/or cost trend histories are presented with respect to the following categories; (1) buildings and structures; (2) construction of complete plant (petroleum refining and processing and electric power generation); (3) component plants and equipments; (4) electric power transmission and distribution; (5) materials; (6) instrumentation and electronics; (7) oceangoing tankers (relevant to OTEC); (8) forest and agricultural products (relevant to biomass); (9) ancillary equipments; (10) labor; and (11) energy. (WHK)« less