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Policy-makers seeking to limit the impact of coal electricity-generating units (EGUs, also known as power plants) on air quality and climate justify regulations by quantifying the health burden attributable to exposure from these sources. We defined “coal PM2.5” as fine particulate matter associated with coal EGU sulfur dioxide emissions and estimated annual exposure to coal PM2.5 from 480 EGUs in the US. We estimated the number of deaths attributable to coal PM2.5 from 1999 to 2020 using individual-level Medicare death records representing 650 million person-years. Exposure to coal PM2.5 was associated with 2.1 times greater mortality risk than exposure to PM2.5 from all sources. A total of 460,000 deaths were attributable to coal PM2.5, representing 25% of all PM2.5-related Medicare deaths before 2009 and 7% after 2012. Here, we quantify and visualize the contribution of individual EGUs to mortality [ABSTRACT FROM AUTHOR]

Surveys of the costs of inputs assigned to pollution abatement (Stated Costs) have been the principal method used to estimate pollution abatement costs. While surveys have been widely used, problems with these surveys may adversely affect their ability to accurately measure pollution abatement costs. In this paper, we propose a method that does not depend on surveys of input costs. Instead, a nonparametric cost function that models the joint production of good and bad outputs is used to identify the cost of inputs assigned to pollution abatement (Revealed Costs). The increased input costs when the bad output is not freely disposable compared to input costs when the bad output is freely disposable constitute our estimate of the revealed cost of pollution abatement. Our model is illustrated using data from coal-fired electric power plants in the United States for 2000–2005. [ABSTRACT FROM AUTHOR]

The scale and pace of energy infrastructure development required to achieve netzero greenhouse gas (GHG) emissions are unprecedented, yet our understanding of how to minimize its potential impacts on land and ocean use and natural resources is inadequate. Using high-resolution energy and land-use modeling, we developed spatially explicit scenarios for reaching an economy-wide net-zero GHG target in the western United States by 2050. We found that among net-zero policy cases that vary the rate of transportation and building electrification and use of fossil fuels, nuclear generation, and biomass, the "High Electrification" case, which utilizes electricity generation the most efficiently, had the lowest total land and ocean area requirements (84,000 to 105,000 km² vs. 88,100 to 158,000 km² across all other cases). Different levels of land and ocean use protections were applied to determine their effect on siting, environmental and social impacts, and energy costs. Meeting the net-zero target with stronger land and ocean use protections did not significantly alter the share of different energy generation technologies and only increased system costs by 3%, but decreased additional interstate transmission capacity by 20%. Yet, failure to avoid development in areas with high conservation value is likely to result in substantial habitat loss. [ABSTRACT FROM AUTHOR]

Policies to reduce greenhouse gases associated with electricity generation have been a major focus of public policy in the United States, but their implications for achieving environmental justice among historically overburdened communities inappropriately remains a marginal issue. In this study we address research gaps in historical and current ambient air emissions burdens in environmental justice communities from power plants participating in the Regional Greenhouse Gases Initiative (RGGI), the country's first market-based power sector emissions reduction program. We find that in RGGI states the percentage of people of color that live within 0–6.2 miles from power plants is up to 23.5 percent higher than the percent of the white population that lives within those same distance bands, and the percentage of people living in poverty that live within 0–5 miles from power plants is up to 15.3 percent higher than the percent of the population not living in poverty within those same distance bands. More importantly, the transition from coal to natural gas underway before RGGI formally started resulted in large increases in both the number of electric-generating units burning natural gas and total net generation from natural gas in environmental justice communities hosting electric-generating units, compared to other communities. Our findings indicate that power sector carbon mitigation policies' focusing on aggregate emissions reductions have largely benefitted non-environmental justice communities and have not redressed the fundamental problem of disparities in pollutant burdens between EJ and non-EJ communities. These must be directly addressed in climate change and carbon emissions mitigation policy. [ABSTRACT FROM AUTHOR]

Building electrification is essential to many full-economy decarbonization pathways. However, current decarbonization modeling in the United States (U.S.) does not incorporate seasonal fluctuations in building energy demand, seasonal fluctuations in electricity demand of electrified buildings, or the ramifications of this extra demand for electricity generation. Here, we examine historical energy data in the U.S. to evaluate current seasonal fluctuation in total energy demand and management of seasonal fluctuations. We then model additional electricity demand under different building electrification scenarios and the necessary increases in wind or solar PV to meet this demand. We found that U.S. monthly average total building energy consumption varies by a factor of 1.6×—lowest in May and highest in January. This is largely managed by fossil fuel systems with long-term storage capability. All of our building electrification scenarios resulted in substantial increases in winter electrical demand, enough to switch the grid from summer to winter peaking. Meeting this peak with renewables would require a 28× increase in January wind generation, or a 303× increase in January solar, with excess generation in other months. Highly efficient building electrification can shrink this winter peak—requiring 4.5× more generation from wind and 36× more from solar. [ABSTRACT FROM AUTHOR]

Between 2010 and 2020, residential solar installations grew at an average rate of 42% per year in the United States with subsidies and promises of rapid payback times contributing to adoption. However, the relationship between geographically localized economic drivers, adoption of residential solar energy, and the impact on carbon emissions remain poorly quantified. Here we assess the geospatial variations in economic payoff and carbon offset within the United States and propose a more efficient geographical roadmap for subsidies focus. The results show that the economic benefits of residential solar depend strongly on local electricity prices and energy mix. We find favorable economics in some regions with low solar irradiance and some sunny locations where residential solar will not be competitive relative to local electricity prices. Similarly, the reduction in the carbon footprint of electricity generation that the adoption of residential solar could provide varies strongly by location. We also identify optimal places for policy deployment and provide helpful data to allow for informed decisions by policymakers. [ABSTRACT FROM AUTHOR]

This paper describes GCAM-USA v5.3_water_dispatch, an open-source model that represents key interactions across economic, energy, water, and land systems in a consistent global framework with subnational detail in the United States. GCAM-USA divides the world into 31 geopolitical regions outside the United States (US) and represents the US economy and energy systems in 51 state-level regions (50 states plus the District of Columbia). The model also includes 235 water basins and 384 land use regions, and 23 of each fall at least partially within the United States. GCAM-USA offers a level of process and temporal resolution rare for models of its class and scope, including detailed subnational representation of US water demands and supplies and sub-annual operations (day and night for each month) in the US electric power sector. GCAM-USA can be used to explore how changes in socioeconomic drivers, technological progress, or policy impact demands for (and production of) energy, water, and crops at a subnational level in the United States while maintaining consistency with broader national and international conditions. This paper describes GCAM-USA's structure, inputs, and outputs, with emphasis on new model features. Four illustrative scenarios encompassing varying socioeconomic and energy system futures are used to explore subnational changes in energy, water, and land use outcomes. We conclude with information about how public users can access the model. [ABSTRACT FROM AUTHOR]

Finding and securing employment is a huge challenge for those who have been released from prison. In this paper, we argue that carbon capture technology carries the unique potential to positively impact employment opportunities for those who are undergoing the reentry process. Notably, these careers exist nearly entirely in industries which already employ ex-felons. If carbon capture technology were implemented throughout the United States, our estimates suggest that ex-felons would be eligible for nearly 3.6 million careers. Many of these jobs would be created in industries which directly or indirectly support natural resource extraction, ethanol production, electricity generation, and iron, steel, and cement production. In addition to benefiting the economy, these careers would provide returning individuals with financial security and supportive, prosocial peer relationships. Accordingly, carbon capture carries the unique ability to promote environmental justice while simultaneously providing relief to a tremendously overburdened criminal justice system. [ABSTRACT FROM AUTHOR]

Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States. [ABSTRACT FROM AUTHOR]

Summary: Many electricity consumers around the world are billed electric peak load charges. In the United States, these demand charges can contribute up to 70% of a consumer's electricity bill. Research has shown that the financial impact of these charges to the consumers can be reduced by acting on the intelligence provided by peak electric load day (PELD) forecasts. Unfortunately, published research detailing PELDs forecasting methodologies for facilities adopting behind the meter renewable electricity generation (BTMREG) is non‐existent. This paper contributes: (a) a PELD forecasting methodology applicable to consumers with BTMREG. A case study demonstrates the methodology's ability to achieve 93% of the potential savings in kW, translating to demand charge reductions of approximately US$ 142 129 per year. (b) The first side‐by‐side performance comparisons of electric load and PELD forecasting models for scenarios with and without BTMREG. (c) The first PELD forecasting model savings comparison for scenarios with and without BTMREG. Experimental results suggest that counterintuitively, BTMREG adoption can translate into higher peak load savings for electricity consumers. [ABSTRACT FROM AUTHOR]

Renewable electricity generation technologies provide a more sustainable solution than the non-renewables. However, as a complete system, renewable energy generation systems have some overall environmental impacts on humankind, resources and ecosystems. This paper will address the environmental effects caused by different types of renewable plants through life-cycle assessment. A comparative study is done among solar PV, biomass, and pumped storage hydropower plants in the United States. Life-cycle impact analysis has been carried out by the Eco-indicator 99, TRACI (Tool for the Reduction and Assessment of Chemical and other Environmental Impacts), CED (Cumulative Energy Demand), Ecopoints 97, RMF (Raw Material Flows) and IPCC (Intergovernmental Panel on Climate Change) methods, using the SimaPro software. The impacts are considered in 10 mid-point impact categories and three end-point indicators. The results show that pumped storage hydropower plants have the highest impact on human health (7.74E-05/kWh) and the ecosystem (3.35E-06/kWh), whereas biomass plants have the maximum effect on resources (4.79E-07/kWh). Overall, the solar PV plants are found to be much more environment-friendly than other renewable electricity generation systems. These findings will guide investors in installing sustainable and clean power plants. • Comparative environmental impacts of solar-PV, biomass and pumped storage hydropower plants was investigated. • Impacts are assessed by a systematic LCA analysis using the ecoinvent database and SimaPro software. • Solar-PV plants are found least hazardous to environment than other renewable energy plants in the United States. • Findings will guide the investors in installing the best renewable power plant considering the environmental aspects. [ABSTRACT FROM AUTHOR]

The U.S. electric power sector has experienced a substantial shift of the generation mix since the turn of the century, moving from heavy reliance on coal‐powered generation to one drawing more from natural gas and, more recently, renewables. This transition has been forged by a mix of macroeconomic factors (recession and recovery); technological breakthroughs (horizontal drilling coupled with hydraulic fracturing; improvements in natural gas plant efficiency); clean energy policies at federal, state, and local levels of government; and private sector demands for carbon‐free energy sources. These factors have combined to reduce carbon emissions from electric power generation substantially this century. In this article we examine the extent of this transition, its causes, as well as the distinct American institutional factors steering it, including energy and environmental federalism, electoral politics, and the political economy of clean energy policy enactment and resistance. [ABSTRACT FROM AUTHOR]

The Weather Research and Forecasting (WRF) Model has been extensively used for wind energy applications, and current releases include a scheme that can be applied to examine the effects of wind turbine arrays on the atmospheric flow and electricity generation from wind turbines. Herein we present a high-resolution simulation using two different wind farm parameterizations: 1) the "Fitch" parameterization that is included in WRF releases and 2) the recently developed Explicit Wake Parameterization (EWP) scheme. We compare the schemes using a single yearlong simulation for a domain centered on the highest density of current turbine deployments in the contiguous United States (Iowa). Pairwise analyses are applied to diagnose the downstream wake effects and impact of wind turbine arrays on near-surface climate conditions. On average, use of the EWP scheme results in small-magnitude wake effects within wind farm arrays and faster recovery of full WT array wakes. This in turn leads to smaller impacts on near-surface climate variables and reduced array–array interactions, which at a systemwide scale lead to summertime capacity factors (i.e., the electrical power produced relative to nameplate installed capacity) that are 2%–3% higher than those from the more commonly applied Fitch parameterization. It is currently not possible to make recommendations with regard to which wind farm parameterization exhibits higher fidelity or to draw inferences with regard to whether the relative performance may vary with prevailing climate conditions and/or wind turbine deployment configuration. However, the sensitivities documented herein to the wind farm parameterization are of sufficient magnitude to potentially influence wind turbine array siting decisions. Thus, our research findings imply high value in undertaking combined long-term high-fidelity observational studies in support of model validation and verification. [ABSTRACT FROM AUTHOR]

As the deployment of wind and solar energy increases in the USA, energy storage (ES) will play an important role in future electric power grids to help manage the variability from high penetration levels of renewable generation, ES can provide promising power/energy demand to coordinate with renewables generation, as a virtual power plant (VPP). There is an industry need for the capability in power system studies to model ternary pumped storage hydropower (T-PSH), a pumped storage technology that offers increased system benefits. This study presents a comprehensive vendor-neutral dynamic model of T-PSH in GE's commercial software positive sequence load flow. A new governor model is developed with detailed gate valve modelling and a shared-penstock function. Specifically, this model is designed to simulate the seamless transition among three operation modes: generation mode, pumping mode, and hydraulic short-circuit mode. The developed T-PSH model has been tested and validated on a 10-bus test system. A comparison study of T-PSH to conventional pumped storage hydropower has also been conducted on the Western interconnection system. [ABSTRACT FROM AUTHOR]

• Modeling method to quantify technology costs required to reach specific deployment. • Nuclear levelized costs of $53–84/MWh required for incremental 1% by 2050. • Concentrating solar power costs of $65–91/MWh required for incremental 1% by 2050. • Offshore wind costs of $39–77/MWh required for incremental 1% by 2050. • More challenging cost targets found with greater penetration due to value decline. Clean energy deployment scenarios typically assume a diverse mix of low-emission generation. However, because of historically low natural gas prices and cost reductions for onshore wind and photovoltaic technologies, recent new capacity deployment, especially in the United States, has come largely from these three generation sources. Here, we quantify competitive cost targets for three less-common zero-emission generation technologies—nuclear, concentrating solar, and offshore wind—under a range of future conditions. We determine the cost targets based on the technologies' system value, such that technology value equals or exceeds its cost. Using a capacity expansion model that develops system-wide, economically optimal generation scenarios of the United States power sector, we find that nuclear, concentrating solar, and offshore wind would need to attain levelized cost ranges of $53–84/MWh, $65–91/MWh, and $39–77/MWh, respectively, to achieve 1% additional grid penetration. We refer to this metric as the "required cost," which is a technology's levelized cost of energy needed to achieve a specific penetration level. Higher penetrations lead to lower required costs as lower-cost generation is displaced. We estimate that to reach 10% penetration, the required cost for nuclear declines to $45–76/MWh. Because of resource variability and increased transmission needs for concentrating solar power and offshore wind, even lower costs are needed to reach higher penetrations: required cost ranges to achieve 10% penetration are estimated to be $30–56/MWh and $18–40/MWh for these two technologies respectively. Our analysis informs research and development priorities and the design of policies supporting clean technologies. [ABSTRACT FROM AUTHOR]

• Across NYS, a wealth of low-value land exists to support utility-scale solar PV. • Solar generation can reduce summer peak demand by up to 9.6% in certain regions in New York. • Regional ramping requirements may increase by up to 151% during sunny winter days. • PV performance during system peak should be retained in capacity valuation of solar. Rapidly growing utility-scale solar photovoltaic (PV) holds promise for addressing the energy and environmental challenges posed by high electricity demand days (HEDDs). We assessed the implications on strategic planning of future solar development in an emerging solar market, New York State (NYS) in the U.S., by synthesizing information on electrical infrastructure, tax assessment, geographical constraints and measured meteorological data. Considering three solar PV penetration scenarios (4500 MW, 6000 MW, and 9000 MW), we examined the impact of distributed utility-scale solar farms on peak demand reduction and ramping requirements during historical peak events. Our results reiterate that, across NYS, a wealth of low-value land exists to support utility-scale solar PV and that generation from these resources can reduce peak demand by up to 9.6% under the 9000 MW scenario. In addition, peak demand reduction displays locational and temporal dependency. Contingent upon local meteorology, a solar farm can reduce demand during the peak hour by anywhere between 10 and 74% of its rated capacity during summer HEDDs. However, the highest ramping requirements are more likely to occur during winter than summer. Furthermore, because developers cannot predict performance during the annual system peak, current capacity valuation methodologies for solar projects may not be adequate to promote a healthy competitive market for solar. Incorporating a broader spectrum of peak demand conditions into variable resource capacity valuation would improve strategic planning, not only in NYS, but across growing solar markets worldwide. [ABSTRACT FROM AUTHOR]

North Korea badly needs energy assistance and has long wanted it in the form of light water reactors, creating a potential bargaining chip in the next round of discussions with Pyongyang. [ABSTRACT FROM AUTHOR]

Decarbonization goals in the United States electricity sector are increasing the levels of renewable energy generation in the electricity supply system, and are driving increased attention to building electrification, which will increase the magnitude and shift the timing of the electricity system peak. These changes are motivating new approaches to coordinate building electricity demand with low-carbon renewable generation, elevating the importance of demand flexibility (DF) in buildings and the need to quantify the temporal impacts of DF. In this paper, we first characterize the hourly predictive accuracy of six commonly used baseline models in an application context of quantifying building-level load shift. Our analysis revealed insights such as hours of the day (afternoons), periods of the week (weekends), and seasons (summer) that were predicted with more accuracy than other time periods. In addition, the analysis showed tendencies toward overprediction or underprediction of load. Secondly, we provide the first published investigation of baseline erosion from repeated dispatch of building load shifting. We observed that as the baseline period is pushed back further from the prediction day, the distribution of errors across baseline model predictions increases, with notable inflection points near the three-week erosion point for two of the three models. [ABSTRACT FROM AUTHOR]

• We incorporate life cycle impacts to energy systems models via monetization. • The cost of leaving the Paris Agreement for the US is 1103 billion USD 2013 in 2030. • Further economic savings could be realized by minimizing life cycle impacts. • Wind onshore is critical for minimizing all environmental impacts concurrently. • The Paris Agreement could induce burden-shifting between sustainability criteria. Current energy systems models focus on cost minimization with a bound on some greenhouse gas emissions. This limited environmental scope can lead to mixes that are not consistent with our sustainable development. To circumvent this limitation, we here make use of the concept of monetization and life cycle assessment to quantify the indirect costs of electricity generation in the design of energy systems. Applying our approach to the United States, we found that the indirect costs of electricity generation could be reduced by as much as 63% by meeting the Paris Agreement. Consequently, the total opportunity cost (i.e., direct and indirect costs) of withdrawing from the Paris Agreement and continuing with the current mix would be as high as 1103 ± 206 billion USD 2013 in 2030 (i.e., 6% of the United States gross domestic product in 2017). By optimizing the direct and indirect costs of electricity generation concurrently, we found an optimal ecological solution that attains total economic savings compared to the Paris Agreement mix of as much as 373 ± 164 billion USD 2013 in 2030. Our work highlights the need to extend the environmental policies that regulate energy systems beyond the direct greenhouse emissions to consider other critical environmental criteria. [ABSTRACT FROM AUTHOR]

This paper discusses the growth of wind power generation in the United States. As wind power has spread, states have used different methods for valuing wind farms for property taxation. Generation of electricity by wind takes two forms: in utility-grade generation, large turbines, usually in farms, are designed to produce electricity for the grid, and in distributed generation, smaller units are not connected to the grid but are designed to generate power for a business, manufacturing complex, agriculture, or local networks. Only utility-grade generation is considered here. The valuation methods used in the principal wind states are described. Also, a more detailed analysis of alternative methods of valuation is presented. Finally, specific issues for assessors to consider in valuing wind farms are discussed. [ABSTRACT FROM AUTHOR]

Abstract The economic viability of new energy technologies is held as a central tenet to their future deployment; conventional wisdom posits economically rational decision-makers will readily invest in proven low-risk and affordable technologies. But what happens when this is not true. This paper examines the non-financial barriers facing economically viable Combined Heat and Power (CHP) projects. CHP is a mature and lower carbon technology that efficiently uses waste heat from thermal electricity generation; CHP can also provide flexibility services to help integrate variable renewable resources. CHP is low risk and many industrialized countries, particularly those in colder climates in Northern Europe and Russia, generate as much as 50% of their electricity and heat needs from CHP, but United States deployment remains low and investment hurdle rates high. While lower U.S. energy costs make some projects un-economic, many economically-viable CHP projects are stalled or killed by non-financial barriers. To better understand why financially viable CHP projects are not getting built, developers, owners and operators, regulators, and other stakeholders of this technology were interviewed and three major barriers emerged a) the business model of the electrical utility b) negative subjective impressions and c) challenges in allocating the risks and benefits. [ABSTRACT FROM AUTHOR]

Wave energy is one of the most concentrated ocean renewable energy resources. Although wave energy has been studied extensively for more than four decades, there is no large commercial installation for wave energy production or a consensus framework on how to exploit this resource. Wave energy is a complex resource that directly depends on two meteorological parameters, which produced significant fluctuations of wave energy in both temporal and spatial criteria. This paper presents a new concept called Energy Event, to analyze meteorological data generated by WaveWatch III over 36 years in the U.S. to characterize and assess wave energy behavior using the peak-over-threshold methodology. This methodology used extreme statistics, segmented the wave energy with different thresholds, and assessed wave energy production on a temporal and spatial framework. Three areas were studied in this paper, including the Gulf of Mexico, the East and West U.S. Coasts. The results indicated that wave energy behaved as a two-state energy system with each state having independent characteristics. The main difference among the three studied areas was the constant baseline of wave power density, with the West Coast having the highest constant baseline and the Gulf of Mexico having the lowest baseline. [ABSTRACT FROM AUTHOR]

Decarbonization is the process of converting our economy from one that runs predominantly on energy derived from fossil fuels to one that runs almost exclusively on clean, carbon-free energy. If pursued on the scale that experts believe necessary to prevent dangerous climate change, the infrastructure changes required to decarbonize the United States will have significant social and cultural implications. States aggressively pursuing decarbonization have adopted policies reflecting their under- standing that decarbonization is a social project implicating numerous value choices. Various state decarbonization policies combine the aim of decarbonization with job promotion, economic development, income redistribution, urban revitalization, open-space preservation, and the continuation of traditional livelihoods. These multifaceted state climate policies are multiplying in the Trump era, as federal alternatives recede. But variegated state policies present a challenge to the smooth functioning of U.S. electricity markets, which operate across states to supply least-cost power on a region-wide basis. To address this friction, regulators at the federal and state levels are considering a novel solution: Perhaps these markets should incorpo- rate the aim of decarbonization rather than leaving this job for the states. There is a clear argument in favor of such reforms--they would allow states to accomplish decarbonization at lower cost while protecting electricity markets from distortionary state policies. Nevertheless, this Article questions the widespread enthusiasm for using regional electricity markets, rather than states, as the primary drivers of decarbonization. Rather than accounting for the social and cultural values at stake in decarbonization, the process of integrating decarbonization into electricity markets prioritizes the aim of least-cost decarbonization above all else--thus rejecting states' more capacious understandings of the goals of decarbonization. Moreover, regional electricity markets are quasi-private, complexly structured membership organizations, which operate under federal oversight and provide lim- ited formal channels for state input. Consequently, if regional electricity markets become the primary locus of decarbonization policy, states will have given away a rich set of policy tools for publicly, creatively, and flexibly managing the trajectory of decarbonization. Understanding decarbonization as a social project thus provides new stakes in the other-wise technocratic debate over electricity markets and climate change, highlighting the importance of maintaining the public voice in critical decisions made around how to decarbonize. [ABSTRACT FROM AUTHOR]

We investigated the accuracy of numerical weather prediction (NWP)-based global horizontal irradiance (GHI) and clear-sky index forecasting over southern Nevada. Accurate forecasts of solar irradiance are required for electric utilities to economically integrate substantial amounts of solar power into their power generation portfolios. Solar irradiance forecasting can enhance the value of renewable energy by anticipating fluctuations in these variable resources. Summertime cloud variability depends largely on the combination of tropical and extratropical synoptic-scale forcing, most of which is observable, predictable, and highly related to the North American Monsoon moisture surge events. We used high-resolution realtime NWP output based on the weather and research forecasting (WRF) model to study the ability of the model to deliver day-ahead GHI and clear-sky index forecasts for a the National Renewable Energy Laboratory (NREL)-University of Nevada site, located in Las Vegas, Nevada. High-resolution forecast products were obtained from the Desert Research Institute (DRI) archived real-time numerical weather forecasting products. Results showed the importance of developing a site-specific seasonal and weather-dependent model output statistics (MOS) approach to improving forecast accuracy, which removes the bias and reduces the overall relative root-mean – square error (rRMSE) of GHI by as much as 6%, when compared to the uncorrected model output; improving forecast accuracy is obtained by adding information that relates regional-scale circulation patterns driving cloudiness, hence irradiance variability to the target area. We show the seasonal dependence of the NWP forecast accuracy and demonstrate that intelligent weather functions provide a pathway to improve accuracy of solar forecasts further. [ABSTRACT FROM AUTHOR]

Given increased policies driving renewable electricity generation and insufficient local production of woody biomass, many countries are reliant upon the importation of wood pellets. Of current wood pellet exports, the vast majority originates from the Southeastern United States (US). In this paper we present results from a cradle-to-gate, attributional process life cycle assessment in which two production scenarios of wood pellets were modelled for the Southeastern US: one utilising roundwood from a silviculture operation and the other utilising sawmill residues. The system boundary includes all steps from harvesting of the wood biomass, through delivery of the finished wood pellets to a US port facility. For each of the impact categories assessed, wood pellets from sawmill residues resulted in higher values, ranging from 5% to 31%. In relation to Global Warming Potential, roundwood pellets resulted in a 13–21% lower value than pellets produced from sawmill residues, depending upon the allocation method. [ABSTRACT FROM AUTHOR]

At Brady Hot Springs, a geothermal field in Nevada, heated fluids have been extracted, cooled, and re-injected to produce electrical power since 1992. Analysis of daily pumping records and catalogs of microseismicity between 2010 and 2015 indicates a statistically significant correlation between days when the daily volume of production was at or above its long-term average rate and days when no seismic event was detected. Conversely, shutdowns in pumping for plant maintenance correlate with increased microseismicity. We hypothesize that the effective stress in the subsurface has adapted to the long-term normal operations (deep extraction) at the site. Under this hypothesis, extraction of fluids inhibits fault slip by increasing the effective stress on faults; in contrast, brief pumping cessations represent times when effective stress is decreased below its long-term average, increasing the likelihood of microseismicity. [ABSTRACT FROM AUTHOR]

The US power sector is in a state of transition, prompted by significant shifts in technological innovations, energy markets, regulatory structures, and social pressures. As the electricity generation fleet changes, so too does the spatial & temporal distribution of the cooling water requirements for power plants. However, to date, these impacts have yet to be quantified. This study uses power plant-specific fuel consumption, generation, and cooling water use data to assess changes in the water withdrawn and consumed by thermoelectric power plants across 8-digit Hydrologic Unit Code (HUC-8) watersheds between 2008 and 2014. During this period, a few prominent trends are noted, including transitions in generation from coal-fired steam to natural-gas combined cycle units, from once-through cooling to wet recirculating towers and dry cooling systems, and from traditional fresh and saline surface cooling water to reclaimed water and groundwater sources. Total US cooling water withdrawals and consumption volume decreased from 2008 to 2014. The average water withdrawn per unit of electrical output decreased over this time, while changes in water consumption rates stayed relatively flat. Changes in water use at the watershed scale were unevenly distributed, as some water-scarce regions experienced increases in cooling water usage for thermal power plants, while others experienced significant water reductions and environmental benefits, especially where coal-fired generation was retired or retrofitted. The results from this study underscore the importance of evaluating water withdrawals and consumption at local spatial scales, as the water extraction, water quality and environmental health consequences of power plants on downstream users are non-uniform. [ABSTRACT FROM AUTHOR]

Water withdrawals for the energy sector are the largest use of fresh water in the United States. Using an econometric model of monthly plant-level electricity generation levels between 2001 and 2012, we estimate the effect of water scarcity on the US electricity fuel mix. We find that hydroelectric generation decreases substantially in response to drought, although this baseline generation is offset primarily by natural gas, depending on the geographic region. We provide empirical evidence that drought can increase emissions of CO 2 and local pollutants. We quantify the social costs of water scarcity to be $330,000 per month for each plant that experiences a one-standard deviation increase in water scarcity (2015 dollars), a relationship that persists under future projections of water scarcity. [ABSTRACT FROM AUTHOR]

This analysis compares the cost of various electric grid scenarios at the national level over a one-year period. Scenarios include high renewable, zero nuclear, zero carbon, and deployment of advanced nuclear. Additionally, several carbon tax scenarios are explored in the model to further assess the cost generation if the current nuclear fleet retired. The cheapest scenarios were those that involved less reliance on conventional nuclear reactors and more molten salt reactors, renewables, or natural gas. [ABSTRACT FROM AUTHOR]

Between 1957 and 1990, nearly 100 nuclear reactors were constructed throughout the U.S., and nuclear power currently accounts for 20 percent of electricity production nationwide. Nuclear plants are often constructed in small communities for which they constitute a large source of employment and income. To date, 24 nuclear reactors have undergone decommissioning, and more are expected in the future, particularly as nuclear reactors age and face increasingly strict regulations. This paper examines the effects of nuclear decommissioning over time at the county-level on measures of employment, income, and population using difference-in-differences regression and propensity score matching. Panel data are obtained from the U.S. Census Bureau, and cover the years 1975-2014. The analysis finds that nuclear decommissioning is associated with positive and statistically significant increases in employment and per capita income over time. Results suggest that nuclear decommissioning may actually be a positive force in regional economic development, and concludes with limitations of the approach and implications for future research. As an emerging area of research, this paper is meant to build on previous work, as well as to provide a basis for further discussion and debate on the economic future of nuclear host communities and regional economies. [ABSTRACT FROM AUTHOR]

Future scenarios and assessment studies used to prepare for long-term energy transitions and develop robust strategies to address climate change are highly dependent on the assessment of technology characteristics and availability. The electric power sector in the United States recently experienced a significant cost escalation: e.g., construction costs for large plants such as nuclear and coal-fired power plants doubled between 2003 and 2007. We assess the main drivers of this escalation. While many factors have affected costs, some of the most significant include cost of materials, particularly the price of metals and to a lesser extent cement, possible increases in labor quantity requirements, the aggressive worldwide competition for power plant design and construction resources, driven by high demand in Asia, market and regulatory changes, and general uncertainty about future regulations and climate policies. We recalibrate power sector technology costs in the Global Change Assessment Model (GCAM) based on an extensive literature review of recent (post-2010) studies and in the process develop a coherent and updated set of current cost and performance assumptions for all major electricity-generating technologies. While current cost and performance assumptions of electricity-generating technologies are key drivers of short-term technology deployment and technology mix in the electricity sector, medium- and long-term deployment pathways are significantly affected by assumed efficiency improvement rates and cost reductions. We develop and demonstrate a method to project efficiency and construction cost of power plants and report a sensitivity analysis to explore the importance of such assumptions in future scenarios generated by GCAM. [ABSTRACT FROM AUTHOR]

Human health and economic prosperity are vulnerable to freshwater shortage in many parts of the world. Despite a growing literature that examines the freshwater vulnerability in various spatiotemporal contexts, existing knowledge has been conventionally constrained by a territorial perspective. On the basis of spatial analyses of monthly water and electricity flows across 2110 watersheds and three interconnected power systems, this study investigates the water-electricity nexus (WEN)'s transboundary effects on freshwater vulnerability in the continental United States in 2014. The effects are shown to be considerable and heterogeneous across time and space. For at least one month a year, 58 million people living in water-abundant watersheds were exposed to additional freshwater vulnerability by relying on electricity generated by freshwater-cooled thermal energy conversion cycles in highly stressed watersheds; for 72 million people living in highly stressed watersheds, their freshwater vulnerability was mitigated by using imported electricity generated in water-abundant watersheds or power plants running dry cooling or using nonfreshwater for cooling purposes. On the country scale, the mitigation effects were the most significant during September and October, while the additional freshwater vulnerability was more significant in February, March, and December. Due to the WEN's transboundary effects, overall, the freshwater vulnerability was slightly worsened within the Eastern Interconnection, substantially improved within the Western Interconnection, and least affected within the ERCOT Interconnection. [ABSTRACT FROM AUTHOR]

This study answers a critical question facing the energy sector in the United States: how does natural gas compare to coal as a climate change mitigation technique? Although natural gas burns cleaner than coal, methane leakage potentially undermines the climate benefits of fuel switching. This study investigates the impact of methane leakage using a novel plant-level lifecycle emissions inventory of greenhouse gas emissions associated with coal mining, transportation, and combustion at 337 existing coal power plants in the United States. Individual plant emissions rates ranged from 901 to more than 2200 kgCO2e/MWh (100-yr GWP); generation-weighted average was 1046 kgCO2e/MWh. Our study finds that the “breakeven” leakage rates for natural gas to have short and long term climate benefits over coal range from 4.4 to 20.9%, depending on the timeframe, plant efficiency, and upstream coal emissions. Emissions benefits can be maximized by replacing highest emitting coal plants with new natural gas plants. Finally, we find fugitive methane emissions can limit carbon reductions from natural gas carbon capture; above 2% leakage, methane leakage reduces CCS benefits by up to half for 20-yr GWP. [ABSTRACT FROM AUTHOR]

Technology costs, state and federal policies and incentives, and local factors such as construction costs and prevailing electricity prices interact to determine the economic favorability of a generation technology in a particular place. To disentangle these factors and better understand how federal policies can make new generation economically viable, we present an integrated multi-technology, state-level project finance model called the Project Finance Mapping Tool and apply it to a variety of policy scenarios. [ABSTRACT FROM AUTHOR]

The economic viability of many U.S. nuclear plants has been deteriorating rapidly since 2010. To save in-state, zero-emission baseload generation, several states have passed zero-emission credits to subsidize their economically challenged plants. Our power market dispatch modeling, however, suggests that keeping nuclear plants online does not necessarily mean a reduction in carbon emissions within the region or state, as the amount of regional emissions also depends on grid characteristics and the evolution of the generation fuel mix. [ABSTRACT FROM AUTHOR]

U.S. renewable electricity resource subsidization program design relies on production-based payments that lower electric energy market prices, often below zero, contrary to the objective of increasing market prices when correcting for an environmental externality. An alternative pricing approach, capacity-based subsidy payments, would substantially reduce the likelihood of negative electric market prices. A more thoughtful examination of the impact of subsidization program design on wholesale power markets is long overdue. [ABSTRACT FROM AUTHOR]

• Fossil fuel-fired power plants' water use may be significantly curtailed by 2035. • Most rivers will see a net increase in streamflow after power plant retirement. • Plant retirement can noticeably increase streamflow over 500 km downstream. • Power plant retirements could make 2.6 km3 of water available for other uses. Nearly two-thirds of fossil fuel-fired electricity generation capacity in the United States is expected to reach its typical end of life by 2035. While the closure of fossil fuel-fired power plants will help advance decarbonization goals, the cessation of water use for fossil fuel-fired power plant cooling - the largest water user in the US - will also impact the nation's water resources. We assess when, where, and how much water will be made available upon the expected retirement of the nation's nearly one thousand fossil fuel-fired power plants by combining a lifespan-based model of fossil fuel-fired generator retirements for the US fossil fuel-fired electricity generation fleet with a national-scale hydrologic model. We show that annual water withdrawals and consumption of fossil fuel-fired power generators will be significantly curtailed (85 % and 68 % reduction, respectively) by 2035 if these generators follow their typical retirement timeline. Most rivers with fossil fuel-fired power plants diverting and/or discharging water will have a net increase in annual streamflow after plant retirement (maximum decrease of 2 %, maximum increase of 57 % by 2050), with the most pronounced increases occurring in the summer months. The retirement of fossil fuel-fired power plants will lead to a large relative change (>5%) in streamflow at least one month per year by 2050 in 31 subbasins. The retirement of power generators was shown to produce noticeable streamflow impacts up to hundreds of kilometers downstream. By the retirement of the last US fossil fuel-fired power generator, 2.6 billion m3 of water that was once consumed by these power plants could be made available for other uses. In addition to the global benefits of reduced greenhouse gas emissions, the notable increases in streamflow and water availability in many US rivers due to the retirement of fossil fuel-fired power plants could benefit local water users and ecosystems. [ABSTRACT FROM AUTHOR]

• Value and cost must be considered for all technologies in evaluating competition. • We quantify technology value at market shares above 50%. • We quantify wind and solar value at combined market shares above 90%. • We explore how technology interactions affect technology value. • We propose methods of parameterizing value in large-scale models. Evaluating competition between electricity technologies is challenging because it depends on both their costs and their values. While technology costs can typically be estimated from projections of the cost components—capital, fuel, and O&M—estimating a technology's value is more complex due to its dependence on its contributions to multiple different grid services, each with prices that can vary substantially over space and time. In this work, using an electricity model of the contiguous United States, we develop relationships between relative value and share of total generation for major electricity generation technologies which, when paired with projections of technology costs, can be used to estimate technology competitiveness. We identify significant differences in the relationship between relative value and generation share for variable renewable energy (VRE) and non-VRE sources, but we demonstrate that all technologies require consideration of their dynamic values (in addition to cost) when evaluating competitiveness. In addition, we demonstrate that relative value of a technology is substantially impacted by not only its own generation share but also other aspects of the system state, in particular the mix of other technologies present in the system. Finally, we use the developed relative value relationships in combination with projections of future technology costs in a coarse resolution model that competes technologies based on a comprehensive competitiveness metric: profitability-adjusted LCOE (PLCOE). We show that this simple representation of technology competition approximately recovers the generation mix from a detailed model, which is not possible using LCOE alone. Such an approach can be used to improve the representation of technology competition in coarse-resolution models such as integrated assessment models, for which simplified metrics are often needed. [ABSTRACT FROM AUTHOR]

Power systems for South and Central America based on 100% renewable energy (RE) in the year 2030 were calculated for the first time using an hourly resolved energy model. The region was subdivided into 15 sub-regions. Four different scenarios were considered: three according to different high voltage direct current (HVDC) transmission grid development levels (region, country, area-wide) and one integrated scenario that considers water desalination and industrial gas demand supplied by synthetic natural gas via power-to-gas (PtG). RE is not only able to cover 1813 TWh of estimated electricity demand of the area in 2030 but also able to generate the electricity needed to fulfil 3.9 billion m3 of water desalination and 640 TWhLHV of synthetic natural gas demand. Existing hydro dams can be used as virtual batteries for solar and wind electricity storage, diminishing the role of storage technologies. The results for total levelized cost of electricity (LCOE) are decreased from 62 €/MWh for a highly decentralized to 56 €/MWh for a highly centralized grid scenario (currency value of the year 2015). For the integrated scenario, the levelized cost of gas (LCOG) and the levelized cost of water (LCOW) are 95 €/MWhLHV and 0.91 €/m3, respectively. A reduction of 8% in total cost and 5% in electricity generation was achieved when integrating desalination and power-to-gas into the system. [ABSTRACT FROM AUTHOR]