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Summary: Wind and solar generation reduce electric sector pollutant emissions and associated climate-related damages and air quality-related health damages. Here, we assess these emission reductions, focusing on carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen oxides (NOx), and incorporate recent estimates of global warming costs and pollution health costs to estimate the dollar value of the associated climate and air quality benefits. From 2019 through 2022, wind and solar generation in the United States provided $249 billion of climate and air quality benefits based on central estimates. In 2022, the normalized benefits were $143/MWh and $100/MWh for wind and solar, respectively, or $36/MWh and $17/MWh when only including air quality benefits. Combined, wind and solar generation led to 1,200 to 1,600 fewer premature mortalities in 2022 (based on a 5th–95th percentile range). Our approach is based on simple, publicly available data, and it includes a sophisticated treatment of uncertainty. Science for society: Wind and solar electricity generation are critical for global decarbonization. Government support for wind and solar generators is often compared with their climate and air quality benefits. To accurately assess these benefits, assessments must be updated to reflect changes to the electricity system and to incorporate the newest research assessing the costs of emissions. For example, recent research finds much higher (>3×) societal costs to carbon emissions compared with commonly used metrics even just a few years ago, and important advances within air pollution epidemiology research have occurred in that time frame as well.We develop a new and reproducible approach to estimate wind and solar climate and air quality benefits in the US using relatively simple and publicly available data and incorporating the recent advances described above. We find benefits are larger than most prior estimates, and they are larger than generation costs, subsidies, and electricity market value.

Abstract In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

Abstract Wind power technology has changed rapidly in recent years. Technology innovation, evolving power markets, and competing land and ocean uses continue to influence the design and operation of wind turbines and plants. Anticipating these trends and their impact on future facilities can inform commercial strategies and research priorities. Drawing from a recent survey of 140 of the world's foremost wind experts, we identify expectations of future wind plant design in 2035, both for onshore and offshore wind. Experts anticipate continued growth in turbine size, to 5.5 (onshore) and 17 MW (offshore), with plants located in increasingly less favorable wind and siting regimes. They expect plant sizes of 1,100 MW for fixed‐bottom and 600 MW for floating offshore wind. Experts forecast enhanced grid‐system value from wind through significant to widespread use of larger rotors, hybrid projects with batteries and hydrogen production, and more. To explain experts' perspectives on future plant design and operation, we identify five mechanisms: economies of unit, plant, and resource scale; grid‐system value economies; and production efficiencies. We characterize learning effects as a moderating influence on the strength of these mechanisms. In combination, experts predict that these design choices support levelized cost of energy reductions of 27% (onshore) and 17%–35% (floating and fixed‐bottom offshore) by 2035 compared to today, while enhancing wind energy's grid service offerings. Our findings provide a much‐needed benchmark for representing future wind technologies in power sector models and address a critical research gap by explaining the economics behind wind energy design choices.

Hybrid power plants, namely those consisting of variable renewable energy (VRE) generators and energy storage in the same location, are growing in popularity and interact differently with the electrical grid than either component would individually. We investigate plant-grid dynamics in highly congested regions to determine whether stand-alone VRE, stand-alone storage, and hybrid VRE-plus-storage plants will reduce or increase the need for nearby transmission. The focus on congested regions offers empirical insight into future grid conditions, as VRE penetration continues to grow. Near congested load centers, we find that hybrid, stand-alone VRE and stand-alone storage plants each reduce transmission value, defined in terms of production costs. On the other hand, in congested areas with high VRE penetration, stand-alone storage and VRE generators have opposing effects, decreasing and increasing the need for transmission, respectively. Importantly, whether or not a hybrid plant’s optimal operation increases or decreases local transmission value depends on the plant’s technological specifications (i.e., lowering degradation costs of battery cycling reduces transmission value) and regulatory environment (i.e., allowing a hybrid to utilize grid charging reduces transmission value). Therefore, technological advances in energy storage and policy decisions will influence which variation of these results are realized. We also assess the financial implications of transmission expansion on hybrid and stand-alone plants. In VRE-rich areas, we find that wind plants stand to gain significantly more from transmission expansion than do solar plants, with a typical energy market revenue increase equal to that from hybridizing with four hours worth of storage. Results are based on real-time nodal price data and location-specific solar and wind generation profiles for 2018–2021 at 23 existing wind and solar plant locations in the United States that experience congestion patterns representative of regions with either high VRE penetration or high demand.

Abstract The past decade of wind power growth was supported by capacity factor improvements and associated cost reductions. But are higher capacity factors a technology success story or, as suggested by recent research, has the influence of technology been overstated by ignoring positive surface wind speed trends? The answer could influence estimates of wind energy's cost and even future deployment rates. We find that US surface wind speed observations imply a 2.6% improvement in capacity factors from 2010 to 2019. Yet newer vintages of wind plants have recorded capacity factors that are ~25% larger than plants built close to 2010. It follows that technological factors and improved site quality, not higher wind speeds, drove most of the improvement in capacity factors. Additionally, we match hundreds of meteorological stations to nearby (

This study is focused on 3D printing of polyamide 6 (PA6), PA6/graphene oxide (PA6/GO) and PA6/glass-fibre-reinforced (PA6/GF) composites. The effect of graphene oxide and glass-fibre reinforcement on 3D-printed PA6 is explored for improvement of the interfacial bond and interlaminar strength in ambient, wet and high temperature conditions relating to electric car battery box requirements. The influence of environmental conditions and process parameters on the 3D-printed polymer composites quality is also examined. Commercial PA6 filament was modified with GO to investigate the thermal and mechanical properties. The modified composites were melt-compounded using a twin-feed extruder to produce an improved 3D-printing filament. The improved filaments were then used to 3D-print test samples for tensile and compression mechanical testing using universal testing machines and thermal characterisation was performed following condition treatment in high temperature and water for correlation to dry/ambient samples. The study results show the studied materials were mostly suitable in dry/ambient conditions. PA6/GF samples demonstrated the highest strength of all three samples in ambient and high-temperature conditions, but the least strength in wet conditions due to osmotic pressure at the fibre/matrix interface that led to fibre breakage. The introduction of 0.1% GO improved the tensile strength by 33%, 11% and 23% in dry/ambient, dry/high temperature and wet/ambient conditions, respectively. The wet PA6/GO samples demonstrated the least strength in comparison to the ambient and high-temperature conditions. Notwithstanding this, PA6/GO exhibited the highest tensile strength in the wet condition, making it the most suitable for a high-strength, water-exposed engineering application.

Summary: Learning curves play a central role in power sector planning. We improve upon past learning curves for utility-scale wind and solar through a combination of approaches. First, we generate plant-level estimates of the levelized cost of energy (LCOE) in the United States, and then use LCOE, rather than capital costs, as the dependent variable. Second, we normalize LCOE to control for exogenous influences unrelated to learning. Third, we use segmented regression to identify change points in LCOE learning. We find full-period LCOE-based learning rates of 15% for wind and 24% for solar, and conclude that (normalized) LCOE-based learning provides a more complete view of technology advancement than afforded by much of the existing literature—particularly that which focuses solely on capital cost learning. Models that do not account for endogenous LCOE-based learning, or that focus narrowly on capital cost learning, may underestimate future LCOE reductions.

The Inflation Reduction Act (IRA) is regarded as the most prominent piece of federal climate legislation in the U.S. thus far. This paper investigates potential impacts of IRA on the power sector, which is the focus of many core IRA provisions. We summarize a multi-model comparison of IRA to identify robust findings and variation in power sector investments, emissions, and costs across 11 models of the U.S. energy system and electricity sector. Our results project that IRA incentives accelerate the deployment of low-emitting capacity, increasing average annual additions by up to 3.2 times current levels through 2035. CO _2 emissions reductions from electricity generation across models range from 47%–83% below 2005 in 2030 (68% average) and 66%–87% in 2035 (78% average). Our higher clean electricity deployment and lower emissions under IRA, compared with earlier U.S. modeling, change the baseline for future policymaking and analysis. IRA helps to bring projected U.S. power sector and economy-wide emissions closer to near-term climate targets; however, no models indicate that these targets will be met with IRA alone, which suggests that additional policies, incentives, and private sector actions are needed.

In 2020, average wholesale electricity prices in the United States fell to $21/MWh, their lowest level since the beginning of the 21st century. Low natural gas prices and the proliferation of low marginal cost resources like wind and solar had already established a trend toward lower wholesale prices, and this trend was exacerbated by declining electricity demand due to the Covid-19 pandemic in 2020. Negative real-time hourly wholesale prices occurred in about 4% of all hours and wholesale market nodes across the United States, but these were not distributed evenly. Regional clusters emerged, for example, in the Permian Basin in western Texas, and in Kansas and western Oklahoma in the Southwest Power Pool (SPP), negative prices accounted for more than 25% of all hours. Negative electricity prices result either from local congestion of the transmission system leading supply to exceed demand locally or due to system-wide oversupply. Looking at the latter condition in SPP, we find that all major generator types contribute to this excess supply, because of limited ramping flexibility or self-scheduled out-of-market unit commitments. Additional monetary production incentives such as renewable energy credits or tax credits also enable negative bids; indeed, negative prices predominantly occur when demand levels are low and wind production levels are high. Frequent negative prices can inform the value of additional renewable energy investments at specific locations, the need for transmission and storage development, and opportunities load growth or adaptation.

Summary: Low- and moderate-income (LMI) households remain less likely to adopt rooftop solar photovoltaics (PV) than higher-income households. A transient period of inequitable adoption is common among emerging technologies but stakeholders are calling for an accelerated transition to equitable rooftop PV adoption. To date, researchers have focused on demand-side drivers of PV adoption inequity, but supply-side factors could also play a role. Here, we use quote data to explore whether PV installers implement income-targeted marketing and the extent to which such strategies drive adoption inequity. We find that installers submit fewer quotes to households in low-income areas and those households that receive fewer quotes are less likely to adopt. The data suggest that income-targeted marketing explains about one-quarter of the difference in PV adoption rates between LMI and higher-income households. Policymakers could explore a broader suite of interventions to address demand- and supply-side drivers of PV adoption inequity.

Offshore wind power deployment has been concentrated in Europe, and remains limited in other areas of the world. Among the many challenges to deployment is the need to understand the value that offshore wind provides within electricity markets. This article develops a rigorous method to assess the economic value of offshore wind along the eastern coastline of the United States, seeking improved understanding of how the value of offshore wind varies both geographically and over time, and what has driven that variation. The article uses historical (2007–2016) weather data at thousands of potential offshore wind sites, combined with historical wholesale electricity market outcomes and renewable energy certificate (REC) prices at hundreds of possible transmission interconnection points. We find that the average historical market value of offshore wind from 2007 to 2016—considering energy, capacity, and RECs—varies significantly by project location, from $40/MWh to more than $110/MWh, and is highest for sites off of New York, Connecticut, Rhode Island, and Massachusetts. As energy and REC prices have fallen in recent years, so too has the market value of offshore wind. The historical value of offshore wind is found to exceed that of onshore wind, due to offshore wind sites being located more favorably in terms of constrained pricing points, and also due to a more-favorable temporal profile of electricity production. Cost reductions that approximate those witnessed recently in Europe may be needed for offshore wind to offer a credible economic value proposition on a widespread basis in the United States.

Renewable portfolio standards (RPS) exist in 29 US states and the District of Columbia. This article summarizes the first national-level, integrated assessment of the future costs and benefits of existing RPS policies; the same metrics are evaluated under a second scenario in which widespread expansion of these policies is assumed to occur. Depending on assumptions about renewable energy technology advancement and natural gas prices, existing RPS policies increase electric system costs by as much as $31 billion, on a present-value basis over 2015−2050. The expanded renewable deployment scenario yields incremental costs that range from $23 billion to $194 billion, depending on the assumptions employed. The monetized value of improved air quality and reduced climate damages exceed these costs. Using central assumptions, existing RPS policies yield $97 billion in air-pollution health benefits and $161 billion in climate damage reductions. Under the expanded RPS case, health benefits total $558 billion and climate benefits equal $599 billion. These scenarios also yield benefits in the form of reduced water use. RPS programs are not likely to represent the most cost effective path towards achieving air quality and climate benefits. Nonetheless, the findings suggest that US RPS programs are, on a national basis, cost effective when considering externalities.