10 research outputs found
Recommended from our members
Income Trends of Residential PV Adopters: An analysis of household-level income estimates
The residential photovoltaic (PV) market has expanded rapidly over the past decade, but questions exist about how equitably that growth has occurred across income groups. Prior studies have investigated this question but are often limited by narrow geographic study regions, now-dated analysis timeframes, or coarse estimates of PV-adopter incomes. At the same time, a spate of new programs and initiatives, as well as innovations in business models and product design, have emerged in recent years with the aim of making solar more accessible and affordable to broader segments of the population. Yet, many of those efforts are proceeding without robust underlying information about the income characteristics of recent residential PV adopters.
This work aims to establish basic factual information about income trends among U.S. residential solar adopters, with some emphasis on low- and moderate-income (LMI) households. The analysis is unique in its relatively extensive coverage of the U.S. solar market, relying on Berkeley Lab’s Tracking the Sun dataset, which contains project-level data for the vast majority of all residential PV systems in the country (a subset of which are ultimately included in the analysis sample). This analysis is also unique in its use of household-level income estimates that provide a more-precise characterization of PV-adopter incomes than in most prior studies
Recommended from our members
Tracking the Sun 10: The Installed Price of Residential and Non-Residential Photovoltaic Systems in the United States
Berkeley Lab’s Tracking the Sun report series is dedicated to summarizing trends in the installed price of grid-connected, residential and non-residential systems solar photovoltaic (PV) systems in the United States. The present report, the tenth edition in the series, focuses on systems installed through year-end 2016, with preliminary data for the first half of 2017. The report provides an overview of both long-term and more-recent trends, highlighting key drivers for installed price declines over different time horizons. The report also extensively characterizes the widespread variability in system pricing, comparing installed prices across states, market segments, installers, and various system and technology characteristics.
The trends described in this report derive from project-level data collected by state agencies and utilities that administer PV incentive programs, solar renewable energy credit (SREC) registration systems, or interconnection processes. In total, data for this report were compiled and cleaned for more than 1.1 million individual PV systems, though the analysis in the report is based on a subset of that sample, consisting of roughly 630,000 systems with available installed price data. The full underlying dataset of project-level data (excluding any confidential information) is available in a public data file, for use by other researchers and analysts
Recommended from our members
Solar + Storage Synergies for Managing Commercial-Customer Demand Charges
Demand charges, which are based on a customer’s maximum demand in kilowatts (kW), are a common element of electricity rate structures for commercial customers. Customer-sited solar photovoltaic (PV) systems can potentially reduce demand charges, but the level of savings is difficult to predict, given variations in demand charge designs, customer loads, and PV generation profiles. Lawrence Berkeley National Laboratory (Berkeley Lab) and the National Renewable Energy Laboratory (NREL) are collaborating on a series of studies to understand how solar PV can impact demand charges. Prior studies in the series examined demand charge reductions from solar on a stand-alone basis for residential and commercial customers. Those earlier analyses found that solar, alone, has limited ability to reduce demand charges depending on the specific design of the demand charge and on the shape of the customer’s load profile. This latest analysis estimates demand charge savings from solar in commercial buildings when co-deployed with behind-the-meter storage, highlighting the complementary roles of the two technologies. The analysis is based on simulated loads, solar generation, and storage dispatch across a wide variety of building types, locations, system configurations, and demand charge designs
Recommended from our members
Sources of price dispersion in U.S. residential solar installations
Prices of solar PV have dropped dramatically, by half in just the past 6 years. But looking simply at prices paid today, there is considerable heterogeneity. For systems installed in 2014, the 10-90 percentile range for the observed $/W spans nearly a factor of 2. This apparent price dispersion raises policy-relevant questions, such as: why are consumers paying more than they need to? And would better-informed consumers increase the social benefits of solar PV? This paper analyzes price dispersion in U.S. residential PV installations between 2008 and 2014. Focusing on the most commonly used metric in previous studies of price dispersion, we use the quarterly coefficient of variation (CV) as our measure of price dispersion. We find higher levels of price dispersion in our data (0.22) than the average of 55 previous studies we reviewed (0.16). We also find that price dispersion has been persistent; it has remained above 0.15 since 2000 with no trend over that period. If anything, price dispersion has been increasing recently during the period for which we have complete data, 2008-14. Econometric analysis of the factors affecting price dispersion supports theories from the economic literature focusing on access to information and the costs and benefits of consumer search. Factors that increase the consumer payoffs of investing time in searching for information—system size and the value of solar—are associated with lower levels of price dispersion. Factors that reduce the costs of search—neighbors who have recently installed solar and having third-party quotes available—are also associated with less price dispersion. These results provide support for the importance of public efforts to enhance access to price information, e.g. by supporting price quote providers. The results also point to the particular need for information in nascent markets for PV in which access to the experience of neighbors is not available
Estimating the Value of Improved Distributed Photovoltaic Adoption Forecasts for Utility Resource Planning
Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities; forecasting capabilities can be improved, but generally at a cost. This paper informs this decision-space by using a suite of models to explore the capacity expansion and operation of the Western Interconnection over a 15-year period across a wide range of DPV growth rates and misforecast severities. The system costs under a misforecast are compared against the costs under a perfect forecast, to quantify the costs of misforecasting. Using a simplified probabilistic method applied to these modeling results, an analyst can make a first-order estimate of the financial benefit of improving a utility’s forecasting capabilities, and thus be better informed about whether to make such an investment. For example, under our base assumptions, a utility with 10 TWh per year of retail electric sales who initially estimates that DPV growth could range from 2% to 7.5% of total generation over the next 15 years could expect total present-value savings of approximately $4 million if they could reduce the severity of misforecasting to within ±25%. Utility resource planners can compare those savings against the costs needed to achieve that level of precision, to guide their decision on whether to make an investment in tools or resources
Recommended from our members
Diffusion of Innovations: Interplay of Social, Economic, Technological, and Policy Drivers in the Solar Industry—Summary of UT Austin Student Capstone Research Projects
The University of Texas at Austin’s Policy Research Project (PRP), a nine-month (two semesters) capstone, is a keystone of the core curriculum at the LBJ School of Public Affairs. In PRPs, small groups of students, under the mentorship of a faculty director, take on real-world problems that require special knowledge and skill sets. PRPs expose students to challenges in formulating and executing research, and in communicating academic research and related complex data to broader stakeholder communities and decision makers. The PRP structure is an innovative and effective approach for integrating research within the teaching and training of graduate students who are preparing themselves to address important real-world problems at the intersection of society, economics, technology, and policy.
The project summaries below describe seven papers developed during September 2017 – May 2018 as part of a PRP on “Diffusion of Innovations: Interplay of Social, Economic, Technological, and Policy Drivers in the Solar Industry.” Twenty graduate students, drawn from the LBJ School’s Masters in Public Affairs and Masters in Global Policy Studies programs and the Jackson School Geoscience’s Energy and Earth Resources program, participated in this PRP. Dr. Varun Rai, Associate Professor and Associate Dean for Research at the LBJ School, directed the PRP, with support from his research team including: Dr. Ariane Beck, Dr. Ashok Sekar, D. Cale Reeves, and Erik Funkhouser. Clients for the project included the U.S. Department of Energy (Casey Canfield), Lawrence Berkeley National Laboratory (Ben Hoen, Galen Barbose Joachim Seel, Naïm Darghouth, Ryan Wiser), and National Renewable Energy Laboratory (Benjamin Sigrin, Eric O’Shaughnessy).
The seven projects separately addressed one of the following topics: (1) low- and middle-income PV adoption, (2) modeling economic and information intervention design, (3) evaluation of DOE’s Solar in Your Community Challenge, (4) property value impacts near large-scale solar facilities, (5) solar market maturity and evolution of business models, (6) social media data for predicting PV adoption, and (7) individual-level variation in adoption of innovations. Many of the papers relied on data collected and curated by Lawrence Berkeley National Laboratory, including data embedded within the annual Tracking the Sun and Utility-Scale Solar reports. Each of the seven teams in the PRP prepared a research paper. The PRP culminated with a full-day conference at UT Austin in May 2018 to present findings from the seven projects in this PRP to a broad audience of about 75 experts from academia, national labs, industry, and government from across the country