Social and communication networks are key determinants in the decision-making of individuals who make up technological systems. In the context of residential photovoltaic (PV) arrays, it would be useful for a range of market players to understand the nature of those networks and how they affect household decision-making to adopt PV.
- What are the main motivations for people to adopt PV technologies?
- How do socio-demographic factors correlate with adoption of PV?
- What financial metrics (such as payback period or rate of return) do PV adopters use to assess the financial merits of PV-based electricity generation?
- What uncertainties and barriers do potential adopters face?
- What information sources (other PV owners, websites, etc.) do consumers use to inform their decision to install PV?
- How effective are these different information channels? and,
- What is the consumer’s post-installation experience in comparison to pre-installation expectations from PV?
Despite the clear importance of these questions, there is little rigorous data and analysis to answer them. With that vacuum in mind, we at the Energy Systems Transformation (EST) Group at the University of Texas at Austin initiated survey-based research to study the residential PV market. The data for the findings reported here were collected during August to November 2011 from 365 residential PV owners in Texas. Separate full-length publications are in preparation with more detailed presentation, analysis and discussion of the research findings.
As expected, the average PV adopter in Texas is more educated and has a higher income than the median Texan. For example, the median household income in 2011 of all respondents is between $85,000 and $115,000. The median household income in 2009 in Texas was $48,286. Regarding motivations, general interest in energy, belief that PV is a financially prudent investment and a desire to reduce environmental footprint were reported as equally important motivators for installing PV (responders consider energy security and energy independence as part of the “general interest in energy”). Many respondents stated that electricity cost has increased and will continue to increase, making PV a better investment with time.
Our research suggests that while there is no dearth of PV-related information for potential adopters, the relevance and trustworthiness of information continues to be an issue. During the decision-making period (DMP) — the time between when a household begins to consider PV seriously and the date when they sign a contract to install a PV system — the respondents seem to have developed a good understanding of the technical as well as financial attributes of PV. In other words, the necessary information is out there.
Yet responders also report spending a significant amount of time and effort sifting through all this information during their DMP—the average DMP reported was nine months (median of six months). Prospective adopters rarely complain about too little information. Instead, they face an information overload that is hard to distill into a coherent picture showing how residential PV will affect them. There is a clear need to consolidate the necessary information and tools into a central information clearinghouse run by an independent, trustworthy third-party.
An effective strategy that several PV adopters employ during their DMP to access trustworthy information—apparently in low supply—is to contact existing PV owners, both in and outside their neighborhood. We saw that 90% of the sample agreed or strongly agreed with the statement “Talking to owners of PV systems was useful or would have been useful.” Of responders who contacted other PV owners prior to installation, 57% agreed that “my discussions with PV owners profoundly improved the quality of information.”
Further, our study shows that potential adopters who had a more difficult time finding dependable information are more likely to want to talk to other PV owners. Contact with neighbors before installation was the single most effective strategy for speeding decision times. On average, those with at least one contact with an existing PV owner in the neighborhood took 4.5 months less in their DMP.
While there is need for the quality of information provided by contact with other owners among potential adopters, this need is not uniform across the spectrum. For example, the solar-leasing model makes information gathering for potential adopters redundant along several dimensions, especially regarding performance and guarantee of the PV system. That is, those who lease do not spend as much time researching any other attribute of solar but finances. This is consistent with the fact that typically performance, as well as operation and maintenance (O&M), of the equipment is covered under the lease agreements, so these aspects do not concern leasers much. On average, leasers report spending less time researching (DMP lower by two months) and report easier availability of dependable information. Consistent with all this, 87% of leasers agree or strongly agree that talking to other PV owners is unnecessary.
So what about the economics of decision-making in the adoption of residential solar PV, especially buy vs. lease differences? Insights on the financial aspects of residential PV as seen from the consumers’ perspective are perhaps the most intriguing. Most adopters (87%) use simple metrics like payback period to evaluate the finances of PV. Reported payback period ranged from 1.5 to 35 years with the majority reporting a range between 7 and 10 years. Few report using net present value (NPV) as a decision metric, even though rational decision-making would suggest the use of NPV. Further, about 40% of the adopters perform the financial calculations by themselves. Given the inherent complexity of reliably calculating a PV system’s lifetime finances, it is likely that majority of these estimates are not accurate. Interestingly still, a majority of the respondents report system performance “as expected or better than expected.”
We compared the payback period that PV adopters report as having used to evaluate their investment decision with an objective model we have built to calculate those same metrics. Our model includes several detailed features of household-level electricity consumption, electricity rates and PV-based electricity generation, including time-of-day and monthly variations. This comparison of reported and objective metrics allows us to unpack the differences in risk perceptions between buyers and leasers of PV. Assuming the same discount (10%) for all adopters, we find that across a range of plausible scenarios buyers are more optimistic in their outlook about the costs and benefits of PV than leasers. That is, either buyers have a lower discount rate compared to leasers, or they believe more strongly that electricity prices will increase at a faster pace than in the past and that O&M costs of their PV system will be small.
Further, we do not find any significant variation between buyers and leasers on any socio-demographic dimension (age, home value, income etc.). Taken together, these findings suggest that the leasing model is making PV adoption possible for households with a tight cash-flow situation, i.e., those with a higher discount rate. From this perspective, the leasing model has opened a new market segment at existing prices and supply chain conditions, and represents a significant business model innovation.
What have we learned about PV-adopters’ post-installation experience? As discussed above, the decision to install a PV system is a resource-intensive process — it requires significant amount of both time and effort as well as capital. Given this relatively intense DMP as compared to most other household decisions, it might be expected that the adoption of PV would lead to a change in awareness of electricity use — when it is used, how it is used and how much is used.
More than 70% of the sample reports that awareness of their electricity use (amount used, bill paid and purpose of use) is “higher or much higher” as a result of installing solar. Thus, most respondents believe that their awareness is higher post-installation in all three areas of electricity use. A variety of factors, including the intensity of information search during the decision-period and the use of monitoring devices post-installation, appear to be in play as awareness enhancers.
A significant portion (46%) of PV adopters perceives that their total electricity consumption (PV + Grid) is lower post-installation than compared to pre-installation. Significantly increased awareness of their electricity usage and an enhanced concern for the environment in the process of PV adoption appear as tentative drivers of these perceptions
Finally, about one-third of the respondents report changing at least part of their electricity-consuming activities post-installation to match more closely electricity production from their PV systems — load-shifting into peak demand hours. Many who reported load-shifting into peak hours report doing so to make “better use” of the electricity generated by the PV system. While we cannot confirm a causal effect here, it is tempting to speculate that the price differential between inflows and outflows drives the load-shifting into peak hours by some PV adopters.
At least, that is how several PV adopters perceive the situation. In some areas surveyed, several retail electricity providers do not provide any payment for outflows to the grid or do so at a lower rate than the rate for electricity inflows from the grid. Several respondents note this and lament that the price differential deprives them of the true value of the electricity generated by their PV system.
Regarding the performance, operation, maintenance and financial attractiveness of their systems, most respondents feel that their PV system is delivering “as expected” or “better than expected.” Overall, PV adopters report to be highly satisfied with their decision to install PV. SPW
By: Varun Rai
Rai is an assistant professor at the LBJ School of Public Affairs and in Mechanical Engineering at the University of Texas at Austin, where he directs the Energy Systems Transformation Research Group, www.ESTresearch.com.