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.

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.

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.

Commercial retail electricity rates commonly include a demand charge component, based on some measure of the customer’s peak demand. Customer-sited solar PV can potentially reduce demand charges, but the magnitude of these savings can be difficult to predict, given variations in demand charge designs, customer loads, and PV generation profiles. Moreover, depending on the circumstances, demand charges from solar may or may not align well with associated utility cost savings. Lawrence Berkeley National Laboratory (Berkeley Lab) and the National Renewable Energy Laboratory (NREL) are collaborating in a series of studies to understand how solar PV can reduce demand charge levels for a variety of customer types and demand charges designs. Previous work focused on residential customs with solar. This study, instead, focuses on commercial customers and seeks to understand the extent and conditions under which rooftop can solar reduce commercial demand charges. To answer these questions, we simulate demand charge savings for a broad range of commercial customer types, demand charge designs, locations, and PV system characteristics. This particular analysis does not include storage, but a subsequent analysis in this series will evaluate demand charge savings for commercial customers with solar and storage.