TODAY’S STUDY: MAKING CITIES SOLAR FRIENDLY
The Impact of City-level Permitting Processes on Residential Photovoltaic Installation Prices and Development Times: An Empirical Analysis of Solar Systems in California Cities
Ryan Wiser and Changgui Dong, April 2013 (Lawrence Berkeley National Laboratory)
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’s 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.
The cost of photovoltaic (PV) systems has declined dramatically (Barbose et al., 2012), opening new and growing markets for solar energy (Bazilian et al., 2013). Recent literature has sought to understand these cost trends (Wiser et al., 2007; Branker et al., 2011; Peters et al., 2011; Hernandez-Moro and Martinez-Duart, 2013) and the variation in costs caused by altered assumptions and market contexts (Zweibel, 2010; Darling et al., 2011; Reichelstein and Yorston, 2013; Seel et al., 2013). Additionally, a substantial literature on learning and experience has been applied to solar energy (e.g., Schaeffer et al., 2004; Soderholm and Sundqvist, 2007; Neij, 2008; van Benthem et al., 2008; Kahouli-Brahmi, 2009; Nemet, 2009; Junginger et al., 2010; Green, 2011). Despite this body of work, further research is required to better understand the geographic scope of learning (Shum and Watanabe, 2008; Martinsen, 2011), to isolate learning-induced cost reductions from the variety of other factors that impact cost trends (e.g., Nemet, 2006; Mukora et al., 2009; Yu et al., 2011), and to explore learning and cost-reduction possibilities for non-hardware balance-of-system costs (Schaeffer et al., 2004; Hoff et al., 2010).
This study builds on this literature by focusing squarely on understanding one component of non-hardware PV costs: the effect ofU.S. city-level permitting processes on the installed price of residential PV systems and on the time required to develop and install those systems.Recent declines in PV system prices have been driven primarily by declining PV module prices (Barbose et al., 2012; Bazilian et al., 2013). As a result, non-hardware business process (or “soft”) costs currently account for well over 50% of the installed price of residential PV systems in the United States, 1 and understanding these costs is crucial for identifying further PV cost-reduction opportunities. City-level permitting processes are one core element of these business process costs, and they potentially add both considerable costs and developmenttime to PV installations. The U.S. Department of Energy (DOE) identified permitting procedures as a barrier to widespread PV deployment and launched the SunShot Rooftop Solar Challenge Program to address this barrier.
A typical PV permitting process in the United States may involve many local government departmental reviews—such as building, electrical, mechanical, plumbing, fire, structural, zoning, and aesthetic reviews—as well as a permitting fee. In addition, site inspections and final approvals are required for permitting (by local agencies) and interconnection (by local utilities) purposes. On the one hand, these permitting processes could add long-term value to the PV industry by protecting consumers, promoting public safety, and rewarding the most diligentinstallers. However, the quantity and diversity of PV permitting documentation requirements, application procedures, inspection processes, and fees used by local jurisdictions complicates the business of PV installers: there are more than 18,000 local jurisdictions in the United States, each with unique and sometimes time-consuming and costly permitting requirements. Clean Power Finance surveyed 273 installers across 12 states and found that more than one third of installers avoid jurisdictions with particularly challenging permitting processes (Tong, 2012). In sum, though permitting procedures do serve important public purposes, onerous procedures may impose unnecessary direct costs (administrative labor and permitting fees) and time on the PV development process and may also raise PV prices by creating entry barriers and thereby restraining competition among PV installers.
Many efforts are underway in the United States to streamline and bring down the cost of local permitting processes. DOE’s Rooftop Solar Challenge is engaging diverse teams of local and state governments along with utilities, installers, non-governmental organizations, and others to make solar energy more accessible and affordable, including by working to reduce administrative barriers to residential and small commercial PV installations. SolarTech, a non-profit industry consortium, developed Solar3.0—A national Platform for Process Innovation to Deliver PV “to increase the competitiveness of solar PV by reducing non-hardware balance-of-system costs by 50% in identified U.S. solar communities by 2014.”4 SolarFreedomNow, a grassroots initiative, advocates a single national policy to cut paperwork and red tape. The DOE-funded Solar America Board for Codes and Standards (Solar ABCs) has developed an expedited permit process for PV systems (Brooks, 2012). Also funded by DOE, Clean Power Finance created a National Solar Permitting Database, an online tool that compiles solar permitting requirements from around the nation.6 In addition, states, such as California and organizations such as the Interstate Renewable Energy Council (IREC) have initiated efforts to expedite permitting and field inspections (OPR, 2012; IREC, 2010). California, Colorado, and a limited number of other states have created caps on the permit fees that can be automatically charged for PV installations, while Vermont uses a streamlined state-wide registration process for PV and eliminates local permitting requirements. Stanfield et al. (2012) describe the diversity of approaches that can and have been used to streamline and lower the cost of local permitting requirements.
Several approaches have been used to compile and analyze the cost impacts of local permitting processes for PV installations. The Sierra Club’s California Solar Permit Fee Campaign collected data to compare permit fees and time requirements across northern and southern California cities (Mills et. al, 2009; Mills and Newick, 2011). Building on the Sierra Club effort, Vote Solar created a Solar Permit Map, with additional city-level permitting data contributed by users (Vote Solar, 2013). A National Renewable Energy Laboratory survey of U.S. PV installers reported that residential PV permitting, inspection, and interconnection (PII) labor costs averaged $0.13/W; with an assumed average permitting fee of $0.09/W, total PII costs averaged $0.22/W(Ardani et al., 2012). This compares with a median total installed price of $6.10/W for PV systems less than 10 kW in size and installed in 2011 (Barbose et al., 2012). Lawrence Berkeley National Laboratory (LBNL) showed that PII costs in Germany averaged only about $0.03/W, almost $0.20/W lower than U.S. costs, owing to Germany’s uniform and simplified regulatory structure (Seel et al., 2013; see also the PVGrid project8). Earlier, Sunrun (2011) estimated that local permitting and inspection could cost $0.50/W in total for a typical residential installation in the United States, or $0.28/W if excluding the impact of permitting on sales and marketing costs as well as variations in building requirements. Only considering the labor costs of permitting (and excluding the permit fee), Clean Power Finance’s recent survey of PV installers yields an average estimate of roughly $0.11/W (Tong, 2012).As for impacts on development times, Clean Power Finance estimates that the average permitting process requires 8 weeks (Tong, 2012). Earlier, Sunrun (2011) reported that PV installation delays as a result of permitting procedures averaged 3.5weeks.
This study addresses two specific research questions. First, how does the permitting process at the city level affect residential PV installation prices, considering not only the permitting fee but also any labor or entry costs borne by PV installers? Second, how does the permitting process determine the time needed to develop a residential PV system? These questions are important because both cost and time requirements are crucial to the market viability of residential PV systems.
To address these questions, this research examines a unique set of detailed permitting data from DOE’s Rooftop Solar Challenge Program, which includes city-level permitting process “scores,” plus data from the California Solar Initiative (CSI) 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. The econometric methods used in this study complement the bottom-up approaches used in previous studies by empirically evaluating the importance of permitting on residential PV installation prices and development times across many cities after controlling for other influential factors, while focusing not on average impacts but rather on the range of impacts observed across cities. The results can further inform efforts to streamline residential PV permitting processes.
The next section describes the data sources used for the present study, followed by descriptions of the econometric models for both installation prices and development times. The next two core sections present results from several different model configurations and an interpretation ofthese results. Finally, conclusions and suggestions for further work are discussed.
Conclusions and Further Work
Non-hardware business process (or “soft”) costs currently account for well over 50% of the installed price of residential PV systems in the United States,and understanding these costs is crucial for identifying further PV cost-reduction opportunities. City-level permitting processes—as one core element of business process costs—appear to have significant effects on installed PVprices and, though the analytical results are less robust, on project development times. Among the sample of California cities analyzed, those with the most favorable permitting processes are found to reduce average residential PV system prices by $0.27–$0.77/W (4%–12% relative to median pricing) and shorten development times by around 24 days (25% compared to the median development time) compared with citieswith the most onerous permitting practices. The range of values depends on the regression model used, and results are more stable and persuasive for price impacts than they are for development-time impacts.
Overall, these cross-city results are consistent with and add to previous attempts to quantify the national or regional average impact of permitting on installed costs and development times (e.g., Sunrun, 2011; Ardani et al., 2012; Clean Power Finance, 2012). In particular, they demonstrate that national or regional average impacts can mask the more substantial impacts that occur at a local level across individual cities.
These findings provide some confirmation that the scoring mechanism used in the DOE Rooftop Solar Challenge is capturing real effects and, more importantly, illustrate the potential benefits of streamlining city-level permitting procedures for residential PV systems. Specifically, our results suggest that, all else being equal, streamlining the permitting process could potentially reduce the price of a 4-kW residential PV system by $1,000 or more, 28 on average, and cut development time by about a month.
As for future research that would extend the analysis presented in this paper, one might expand the geographic reach of the present study to additional cities both within and outside of California. As sample size grows, it may also be appropriate to expand the analysis to include larger, commercial PV installations. Because the development-time results presented in this study are weaker than those for installed prices, further effort to improve the robustness of those results is warranted. Moving beyond installed prices and development times, it may also be useful to assess the impact of permitting on the amount of PV installed at the city level and/or PV installers’ interest in those cities. And, once multiple years of data on permitting scores are available, it may be possible to evaluate more directly the impact of the Rooftop Solar Challenge Program on all of these permitting-impact variables. Finally, one might use methods similar to those applied in this study to investigate other PV soft costs beyond permitting…
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