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Relatively little research exists estimating the marginal impacts of photovoltaic (PV) energy systems on home sale prices. Using a large data set of California homes that sold from 2000 through mid‐2009, we find strong evidence, despite a variety of robustness checks, that existing homes with PV systems sold for a premium over comparable homes without PV systems, implying a near full return on investment. Premiums for new homes are found to be considerably lower than those for existing homes, implying, potentially, a trade‐off between price and sales velocity. The results have significant implications for homeowners, builders, appraisers, lenders, and policymakers. (JEL R31, D12, C33)

Benefits analysis of US Federal government funded research, development, demonstration,and deployment (RD3) programmes for renewable energy (RE) technology improvement typically employs a deterministic forecast of the cost and performance of renewable and nonrenewable fuels. The benefits estimate for a programme derives from the difference betweentwo forecasts, with and without the RD3 in place. The deficiencies of the current approachare threefold: (1) it does not consider uncertainty in the cost of non-renewable energy (NRE), and the option or insurance value of deploying RE if and when NRE costs rise; (2) it does not consider the ability of the RD3 manager to adjust the RD3 effort to suit the evolving state of the world, and the option value of this flexibility; and (3) it does not consider the underlying technical risk associated with RD3, and the impact of that risk on the programme's optimal level of RD3 effort. In this paper, a rudimentary approach to determining the option value of publicly funded RE RD3 is developed. The approach seeks to tackle the first deficiency noted above by providing an estimate of the options benefit of an RE RD3 programme in a future with uncertain NRE costs. While limited by severe assumptions, a computable lattice ofoptions values reveals the economic intuition underlying the decision-making process. An illustrative example indicates how options expose both the insurance and timing values inherent in a simplified RE RD3 programme that coarsely approximates the aggregation of current Federal RE RD3. This paper also discusses the severe limitations of this initial approach, and identifies needed model improvements before the approach can adequately respond to the RE RD3 analysis challenge.

As concerns about social equity and clean energy rise, state and local governments, utilities, and non-profit organizations are offering at least 41 active programs in 21 states to promote solar adoption as a way to reduce energy bills for low- and moderate-income (LMI) households while meeting other policy goals such as job creation and clean energy generation. A new study from Berkeley Lab looks at how those programs are being evaluated. The report provides background on how they seek to address LMI household energy burdens and gives a brief discussion of the art and science of program evaluation, drawn from decades of experience in energy efficiency programs. It then turns to how LMI solar programs are currently being evaluated, highlighting trends among evaluation methods, metrics tracked, and best practices employed. A few programs are explored in more depth to illustrate notable practices that could be applied to other program evaluations. These LMI solar programs are mostly young, operate on tight budgets, and vary considerably in their design and stated goals. Consequently, well-designed program evaluation is critical to better understand what works, what could be improved, and how to maximize program impacts under budget constraints.

As concerns about social equity and clean energy rise, state and local governments, utilities, and non-profit organizations are offering at least 41 active programs in 21 states to promote solar adoption as a way to reduce energy bills for low- and moderate-income (LMI) households while meeting other policy goals such as job creation and clean energy generation. A new study from Berkeley Lab looks at how those programs are being evaluated. The report provides background on how they seek to address LMI household energy burdens and gives a brief discussion of the art and science of program evaluation, drawn from decades of experience in energy efficiency programs. It then turns to how LMI solar programs are currently being evaluated, highlighting trends among evaluation methods, metrics tracked, and best practices employed. A few programs are explored in more depth to illustrate notable practices that could be applied to other program evaluations. These LMI solar programs are mostly young, operate on tight budgets, and vary considerably in their design and stated goals. Consequently, well-designed program evaluation is critical to better understand what works, what could be improved, and how to maximize program impacts under budget constraints.

Sharply reducing carbon emissions is imperative to prevent the worst effects of climate change. Yet even in the power sector—often viewed as the lynchpin to economy-wide decarbonization, and where low-carbon solutions are increasingly plentiful and cost-effective—the pace and scale of the required transformation can be daunting. A review of historical trends, however, shows the progress the power sector has already made in reducing emissions. Fifteen years ago, many business-as-usual projections anticipated that annual carbon dioxide (CO2) emissions from power supply in the United States would reach 3,000 million metric tons (MMT) in 2020. In fact, direct power-sector CO2 emissions in 2020 were 1,450 MMT—roughly 50% below the earlier projections. By this metric, in only 15 years the country's power sector has gone halfway to zero emissions. Other metrics also evolved differently than projected: total consumer electricity costs (i.e., bills) were 18% lower; costs to human health and the climate were 92% and 52% lower, respectively; and the number of jobs in electricity generation was 29% higher. Economic, technical, and policy factors contributed to this success, including sectoral changes, energy efficiency, wind and solar, continued operations of the nuclear fleet, and coal-to-gas fuel switching. This historical record demonstrates the ability of technological and policy changes to set the power sector on a dramatically different emissions trajectory. Past success, however, does not trivialize the challenges that remain for further decarbonization in the power sector and beyond. Nor does it offer a specific roadmap for how best to achieve additional power-sector emissions reductions. Numerous challenges confront a zero-emissions pathway, and future strategies will likely differ from those of the past. Many recent studies have assessed how to make further progress in decarbonizing the power sector on the pathway to decarbonizing the economy as a whole. We summarize the core results of those studies, but the primary goal of this report is to highlight the progress that has already been made in reducing power-sector emissions. As the country maps out a plan for further decarbonization, experience from the past 15 years offers two central lessons. First, policy and technology advancement are imperative to achieving significant emissions reductions. Second, our ability to predict the future is limited, and so it will be crucial to adapt as we gain policy experience and as technologies advance in unexpected ways.

Sharply reducing carbon emissions is imperative to prevent the worst effects of climate change. Yet even in the power sector—often viewed as the lynchpin to economy-wide decarbonization, and where low-carbon solutions are increasingly plentiful and cost-effective—the pace and scale of the required transformation can be daunting. A review of historical trends, however, shows the progress the power sector has already made in reducing emissions. Fifteen years ago, many business-as-usual projections anticipated that annual carbon dioxide (CO2) emissions from power supply in the United States would reach 3,000 million metric tons (MMT) in 2020. In fact, direct power-sector CO2 emissions in 2020 were 1,450 MMT—roughly 50% below the earlier projections. By this metric, in only 15 years the country's power sector has gone halfway to zero emissions. Other metrics also evolved differently than projected: total consumer electricity costs (i.e., bills) were 18% lower; costs to human health and the climate were 92% and 52% lower, respectively; and the number of jobs in electricity generation was 29% higher. Economic, technical, and policy factors contributed to this success, including sectoral changes, energy efficiency, wind and solar, continued operations of the nuclear fleet, and coal-to-gas fuel switching. This historical record demonstrates the ability of technological and policy changes to set the power sector on a dramatically different emissions trajectory. Past success, however, does not trivialize the challenges that remain for further decarbonization in the power sector and beyond. Nor does it offer a specific roadmap for how best to achieve additional power-sector emissions reductions. Numerous challenges confront a zero-emissions pathway, and future strategies will likely differ from those of the past. Many recent studies have assessed how to make further progress in decarbonizing the power sector on the pathway to decarbonizing the economy as a whole. We summarize the core results of those studies, but the primary goal of this report is to highlight the progress that has already been made in reducing power-sector emissions. As the country maps out a plan for further decarbonization, experience from the past 15 years offers two central lessons. First, policy and technology advancement are imperative to achieving significant emissions reductions. Second, our ability to predict the future is limited, and so it will be crucial to adapt as we gain policy experience and as technologies advance in unexpected ways.

In the United States, there has been substantial recent growth in wind energy generating capacity, with growth averaging 24 percent annually during the past five years. About 1,700 MW of wind energy capacity was installed in 2001, while another 410 MW became operational in 2002. This year (2003) shows promise of significant growth with more than 1,500 MW planned. With this growth, an increasing number of states are experiencing investment in wind energy projects. Wind installations currently exist in about half of all U.S. states. This paper explores the key factors at play in the states that have achieved a substantial amount of wind energy investment. Some of the factors that are examined include policy drivers, such as renewable portfolio standards (RPS), federal and state financial incentives, and integrated resource planning; as well as market drivers, such as consumer demand for green power, natural gas price volatility, and wholesale market rules.

This paper presents work by the International Energy Agency's Task 26 'Cost of Wind Energy' on technological and cost trends in land-based wind energy in six participating countries (Denmark, Germany, Ireland, Norway, Sweden, United States) and the European Union between 2008 and 2016. Results indicate that there is a general trend towards larger, taller machines with lower specific powers resulting in higher capacity factors, despite small falls in new site wind resources in most countries, while wind project capital costs and project finance costs also fell. This resulted in an average levelized cost of energy (LCOE) fall of 33% for new projects to 48€/MWh at the end of the study period. Analysis of the components of levelized cost change indicated that changes in specific power, financing cost and capital cost accounted for 45%, 25% and 17% respectively of the estimated reduction. It is therefore important that trends in technological factors such as specific power are considered when assessing wind energy learning rates, rather than just capital costs, which has been the primary focus heretofore. While LCOEs have fallen, the value of wind energy has fallen proportionately more, meaning grid parity appears no closer than at the beginning of the study. Policymakers must therefore consider both the cost and value of wind energy, and understand the volatility of this gap when designing land-based wind energy policy measures.

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.