CO2 emissions associated with electric vehicle charging: The impact of electricity generation mix, charging infrastructure availability and vehicle type
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The reliability of power grids in the future will depend on how system planners account for the integration of new technologies, extreme weather events, and uncertainties in demand growth from increased electrification and data centers. This study introduces an open-source, multisectoral, multiscale modeling framework that projects grid stress and reliability trends between 2020 and 2055 in the Western Interconnection of the United States. The framework integrates global to national energy-water-land dynamics with power plant siting and hourly grid operations modeling. We analyze future wholesale electricity price shocks and unserved energy events across eight scenarios spanning a range of population growth and economic change, generation mixes, and weather conditions. Our results show future grids with high percentage of non-renewable generation and strong economic growth are characterized by higher reliability and lower wholesale electricity prices than lower growth scenarios because of larger reliance on dispatchable generators and lower fossil fuel extraction costs. Scenarios with high percentage of renewable resources have lower median but more volatile wholesale electricity prices as well as more frequent and severe unserved energy events compared to scenarios relying more on dispatchable generators. These events occur because higher proportion of solar and wind energy causes net demand curves to deepen during midday (duck curves get progressively severe), exacerbating the challenge of meeting demand during summer evening peaks. This study suggests that robust and co-optimized transmission and energy storage planning could help maintain low wholesale electricity prices and high reliability levels in future electricity grids across uncertainties in generation mixes.
Four-wave-mixing stimulated Raman scattering (SRS) generation of Stokes and anti-Stokes components in BaWO{sub 4} and SrWO{sub 4} crystals excited by a 1064-nm pulsed laser with a pulse duration of 18 ps has been investigated. It is shown that, due to the four-wave mixings of SRS components in short ({approx}1 cm) crystals, the generation thresholds of the second and third Stokes components are much lower than the values determined by the cascade SRS mechanism. If the crystal length is increased by a factor of more than four, the mechanism of multiwave SRS becomes similar to the cascade mechanism (without four-wave mixings). Rotation of BaWO{sub 4} crystal makes it possible to control the competition of the processes of four-wave-mixing SRS generation of anti-Stokes and second Stokes components. (nonlinear optical phenomena)
The Schelling model of residential segregation has demonstrated that even the slightest preference for neighbors of the same race can be amplified into community-wide segregation. However, these models are unable to simulate mixed, coexisting patterns of segregation and integration, which have been seen to exist in cities. Using evolutionary model discovery we demonstrate how including social factors beyond racial bias when modeling relocation behavior enables the emergence of strongly mixed patterns. Our results indicate that the emergence of mixed patterns is better explained by multiple factors influencing the decision to relocate; the most important being the interaction of nonlinear, rapidly diminishing racial bias with a recent, historical tendency to move. Additionally, preference for less isolated neighborhoods or preference for neighborhoods with longer residing neighbors may produce weaker mixed patterns. Finally, this work highlights the importance of exploring the influence of multiple hypothesized factors of decision making, and their interactions, within agent rules, when studying emergent outcomes generated by agent-based models of complex social systems.
With the aim of reducing greenhouse gas emissions associated with the transportation sector, policy-makers are supporting a multitude of measures to increase electric vehicle adoption. The actual level of emission reduction associated with the electrification of the transport sector is dependent on the contexts that determine when and where drivers charge electric vehicles. This analysis contributes to our understanding of the degree to which a particular electricity grid profile, vehicle type, and charging patterns impact CO2 emissions from light-duty, plug-in electric vehicles. We present an analysis of emissions resulting from both battery electric and plug-in hybrid electric vehicles for four charging scenarios and five electricity grid profiles. A scenario that allows drivers to charge electric vehicles at the workplace yields the lowest level of emissions for the majority of electricity grid profiles. However, vehicle emissions are shown to be highly dependent on the percentage of fossil fuels in the grid mix, with different vehicle types and charging scenarios resulting in fewer emissions when the carbon intensity of the grid is above a defined level. Restricting charging to off-peak hours results in higher total emissions for all vehicle types, as compared to other charging scenarios.
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The absorbed light spectral composition determines the type of carrier generation: interband generation or mixed generation that also includes the generation of electrons from levels of the valence-band tail. The generation type affects the value and temperature dependence of the electron recombination rate in a-Si:H layered films. This effect is caused by a variation in the occupation of the levels of silicon dangling bonds and the valence band tail with electrons upon a change in the carrier generation type. As a result, in the case of mixed carrier generation in the investigated films with a low concentration of native dangling bonds, electron recombination in the films is slow and recombination at the levels of the valence-band tail can prevail up to room temperature.
A Python package to convert the static generation mix from the electricity baseline (i.e., ElectricityLCI) to a residual mix by removing generation amounts from the mix that were used for voluntary renewable electricity certificate (REC) sales.
We study the impact of fuel prices, technology innovation, and a CO2 emissions reduction policy on both the electric power and end-use sectors by comparing outputs from four U.S. energy-economic models through the year 2050. Achieving innovation goals decreases CO2 emissions in all models, regardless of natural gas price, due to increased energy efficiency and low-carbon generation becoming more cost competitive. For the models that include domestic natural gas markets, achieving innovation goals lowers wholesale electricity prices, but this effect diminishes as projected natural gas prices increase. Higher natural gas prices lead to higher wholesale electricity prices but fewer coal capacity retirements. A CO2 electric power sector emissions cap influences electric sector evolution under reference technology assumptions but has little to no incremental influence when added to innovation goals. Long-term, meeting innovation goals achieves a generation mix with similar CO2 emissions compared to the CO2 policy but with smaller increases to wholesale electricity prices. In the short-term, the relative effect on wholesale prices differs by model. Finally, higher natural gas prices, achieving innovation goals, and the combination of the two, increases the amount of renewable generation that is cost-effective to build and operate while slowing the growth of natural-gas fired generation, which is the predominant generation type in 2050 under reference conditions.
In the scenario with four quark generations, we perform a fit using flavor-physics data and determine the allowed values - preferred central values and errors - of all of the elements of the 4x4 quark-mixing matrix. In addition to the direct measurements of some of the elements, we include in the fit the present measurements of several flavor-changing observables in the K and B systems that have small hadronic uncertainties, and also consider the constraints from the vertex corrections to Z{yields}bb. The values taken for the masses of the fourth-generation quarks are consistent with the measurements of the oblique parameters and perturbativity of the Yukawa couplings. We find that |V-tilde{sub tb}|{>=}0.98 at 3{sigma}, so that a fourth generation cannot account for any large deviation of |V{sub tb}| from unity. The fit also indicates that all the new-physics parameters are consistent with zero, and the mixing of the fourth generation with the other three is constrained to be small: we obtain |V-tilde{sub ub}{sup '}|<0.06, |V-tilde{sub cb}{sup '}|<0.027, and |V-tilde{sub tb}{sup '}|<0.31 at 3{sigma}. Still, this does allow for the possibility of new-physics signals in B{sub d}, B{sub s} and rare K decays.
It is now well established that linear and nonlinear instability waves play a significant role in the noise generation process for a wide variety of shear flows such as jets or mixing layers. In that context, the problem of acoustic radiation generated by spatially growing instability waves of two-dimensional subsonic and supersonic mixing layers are revisited in a global point of view, i.e., without any assumption about the base flow, in both a linear and a nonlinear framework by using global and Koopman mode decompositions. In that respect, a timestepping technique based on disturbance equations is employed to extract the most dynamically relevant coherent structures for both linear and nonlinear regimes. The present analysis proposes thus a general strategy for analysing the near-field coherent structures which are responsible for the acoustic noise in these configurations. In particular, we illustrate the failure of linear global modes to describe the noise generation mechanism associated with the vortex pairing for the subsonic regime whereas they appropriately explain the Mach wave radiation of instability waves in the supersonic regime. By contrast, the Dynamic Mode Decomposition (DMD) analysis captures both the near-field dynamics and the far-field acoustics with a few number of modes for both configurations. In addition, the combination of DMD and linear global modes analyses provides new insight about the influence on the radiated noise of nonlinear interactions and saturation of instability waves as well as their interaction with the mean flow.
Wind power forecasting is an important tool in power system operations to address variability and uncertainty. Accurately doing so is important to reducing the occurrence and length of curtailment, enhancing market efficiency, and improving the operational reliability of the bulk power system. This research quantifies the value of wind power forecasting improvements in the IEEE 118-bus test system as modified to emulate the generation mixes of Midcontinent, California, and New England independent system operator balancing authority areas. To measure the economic value, a commercially available production cost modeling tool was used to simulate the multi-timescale unit commitment (UC) and economic dispatch process for calculating the cost savings and curtailment reductions. To measure the reliability improvements, an in-house tool, FESTIV, was used to calculate the system's area control error and the North American Electric Reliability Corporation Control Performance Standard 2. The approach allowed scientific reproducibility of results and cross-validation of the tools. A total of 270 scenarios were evaluated to accommodate the variation of three factors: generation mix, wind penetration level, and wind fore-casting improvements. The modified IEEE 118-bus systems utilized 1 year of data at multiple timescales, including the day-ahead UC, 4-hour-ahead UC, and 5-min real-time dispatch. The value of improved wind power forecasting was found to be strongly tied to the conventional generation mix, existence of energy storage devices, and the penetration level of wind energy. The simulation results demonstrate that wind power forecasting brings clear benefits to power system operations.
The growing dependence in the U.S. on foreign crude oil supplies and increased concerns regarding greenhouse gas emission has generated considerable interest in research to develop renewable and environmentally friendly liquid hydrocarbon transportation fuels. One of the strategies for achieving this is to produce intermediate compounds such as alcohols and other simple oxygenates from biomass generated synthesis gas (mixture of carbon monoxide and hydrogen) and further convert them into liquid hydrocarbons. The focus of this research is to investigate the effects of mixed oxygenates intermediate product compositions on the conversion step to produce hydrocarbon liquids. A typical mixed oxygenate stream is expected to contain water (around 50%), alcohols, such as methanol and ethanol (around 35%), and smaller quantities of oxygenates such as acetaldehyde, acetic acid and ethyl acetate. However the ratio and the composition of the mixed oxygenate stream generated from synthesis gas vary significantly depending on the catalyst used and the process conditions. Zeolite catalyzed deoxygenation of methanol accompanied by chain growth is well understood under Methanol-to-Gasoline (MTG) like reaction conditions using an H-ZSM-5 zeolite as the catalyst6-8. Research has also been conducted to a limited extent in the past with higher alcohols, but not with other oxygenates present9-11. Also there has been little experimental investigation into mixtures containing substantial amounts of water. The latter is of particular interest because water separation from the hydrocarbon product would be less energy intensive than first removing it from the oxygenate intermediate stream prior to hydrocarbon synthesis, potentially reducing overall processing costs.
The value of improving wind power forecasting accuracy at different electricity market operation timescales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios, considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was compared through the diversity of generation mix, the percentage of must-run baseload generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Lastly, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the value of improved wind power forecasting were also analyzed.
This research presents a systematic approach to evaluating the costs of integrating new generation and operational procedures into an existing power system, and the methodology is independent of the type of change or nature of the generation. The work was commissioned by the U.S. Department of Energy and performed by the National Renewable Energy Laboratory to investigate three integration cost-related questions: (1) How does the addition of new generation affect a system's operational costs, (2) How do generation mix and operating parameters and procedures affect costs, and (3) How does the amount of variable generation (non-dispatchable wind and solar) impact the accuracy of natural gas orders? A detailed operational analysis was performed for seven sets of experiments: variable generation, large conventional generation, generation mix, gas prices, fast-start generation, self-scheduling, and gas supply constraints. For each experiment, four components of integration costs were examined: cycling costs, non-cycling VO&M costs, fuel costs, and reserves provisioning costs. The investigation was conducted with PLEXOS production cost modeling software utilizing an updated version of the Institute of Electrical and Electronics Engineers 118-bus test system overlaid with projected operating loads from the Western Electricity Coordinating Council for the Sacramento Municipal Utility District, Puget Sound Energy, and Public Service Colorado in the year 2020. The test system was selected in consultation with an industry-based technical review committee to be a reasonable approximation of an interconnection yet small enough to allow the research team to investigate a large number of scenarios and sensitivity combinations. The research should prove useful to market designers, regulators, utilities, and others who want to better understand how system changes can affect production costs.
The standard scenarios match (sssmatch) tool accepts limited information about an existing transmission system model and computes a new generation mix based on a.) matching a particular NREL Standard Scenario generation mix and b.) minimizing the distance between the system’s original mix and the final one. The distance metric is computed on a nodal basis.
When someone mentions integration costs, thoughts of the costs of integrating renewable generation into an existing system come to mind. We think about how variability and uncertainty can increase power system cycling costs as increasing amounts of wind or solar generation are incorporated into the generation mix. However, seldom do we think about what happens to system costs when new baseload generation is added to an existing system or when generation self-schedules. What happens when a highly flexible combined-cycle plant is added? Do system costs go up, or do they go down? Are other, non-cycling, maintenance costs impacted? In this paper we investigate six technologies and operating practices--including VG, baseload generation, generation mix, gas prices, self-scheduling, and fast-start generation--and how changes in these areas can impact a system's operating costs. This paper provides a working definition of integration costs and four components of variable costs. It describes the study approach and how a production cost modeling-based method was used to determine the cost effects, and, as a part of the study approach section, it describes the test system and data used for the comparisons. Finally, it presents the research findings, and, in closing, suggests three areas for future work.
Abstract We present the results of an experiment investigating the generation of high-order harmonics by a femtosecond near-infrared (NIR) laser pulse in the presence of an extreme ultraviolet (XUV) field provided by a free-electron laser (FEL), a process referred to as XUV-assisted high-order harmonic generation (HHG). Our experimental findings show that the XUV field can lead to a small enhancement in the harmonic yield when the XUV and NIR pulses overlap in time, while a strong decrease of the HHG yield and a red shift of the HHG spectrum is observed when the XUV precedes the NIR pulse. The latter observations are in qualitative agreement with model calculations that consider the effect of a decreased number of neutral emitters but are at odds with the predicted effect of the correspondingly increased ionization fraction on the phase matching. Our study demonstrates the technical feasibility of XUV-assisted HHG experiments at FELs, which may provide new avenues to investigate correlation-driven electron dynamics as well as novel ways to study and control propagation effects and phase matching in HHG.