Electrification Futures Study Demand-side Scenarios report figure data
The file includes the data for figures in the Electrification Futures Study demand-side scenarios report. Additional information on the data can be found in the report.
SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The file includes the data for figures in the Electrification Futures Study demand-side scenarios report. Additional information on the data can be found in the report.
The file includes the data for figures in the Electrification Futures Study end-use electric technologies report. Additional information on the data can be found in the report.
The 10-12 April 2019 thundersnow (i.e., lightning within snowfall) outbreak was examined via ground- and space-based lightning observations and was simulated using a numerical weather prediction model with an explicit electrification parameterization. When compared to observations, the simulation propagated the synoptic snowband two to six hours faster while also exaggerating the 3-D reflectivity structure. Throughout the event, the simulation produced 1,733 thundersnow flashes which was less than what was observed by ground- and space-based lightning sensors. In general, simulated thundersnow flashes were spatially offset from the largest reflectivities within the synoptic snowband and tended to occur within elevated convection that traversed isentropically along the top of mid-level frontogenesis. These simulated thundersnow flashes were associated with a tripole charge structure with ice/snow hydrometeors contributing most to the main negative charge region. Both simulated and observed thundersnow flashes initiated in conditionally unstable environments. Lastly, a conceptual model was developed to explain the spatial separation between the largest reflectivities in the snowband and the occurrence of thundersnow. It is hypothesized that the spatial offset of thundersnow initiation from the reflectivity cores within the synoptic snowband arose from a thermal circulation – induced by mid-level frontogenesis – that advects positively charged ice/snow hydrometeors towards the surface and creates a nearly homogeneous vertical charge structure.
The Fleet Test and Evaluation Team at the U.S. Department of Energy's National Renewable Energy Laboratory is evaluating and documenting the use of shorepower at 50 planned American Recovery and Reinvestment Act (ARRA)-funded truck stop electrification sites across the nation. Trucks participating in the study have idle-reduction equipment installed that was purchased with rebates through the ARRA. A total of 5,000 rebates will be approved.
The Fleet Test and Evaluation Team at the U.S. Department of Energy's National Renewable Energy Laboratory is evaluating and documenting the use of shorepower at 50 planned American Recovery and Reinvestment Act (ARRA)-funded truck stop electrification (TSE) sites across the nation. Trucks participating in the study have idle-reduction equipment installed that was purchased with rebates through the ARRA. A total of 5,000 rebates will be approved. the ARRA. A total of 5,000 rebates will be approved.
The Fleet Test and Evaluation Team at the U.S. Department of Energy's National Renewable Energy Laboratory is evaluating and documenting the use of shorepower at 50 planned American Recovery and Reinvestment Act (ARRA)-funded truck stop electrification (TSE) sites across the nation. Trucks participating in the study have idle-reduction equipment installed that was purchased with rebates through the ARRA. A total of 5,000 rebates will be approved.
Ride-hailing activity is rapidly increasing, largely due to the growth of transportation network companies such as Uber and Lyft. However, traditional taxi companies continue to represent an important mobility option for travelers. Columbus Yellow Cab, a taxi company in Columbus, Ohio, offers traditional line-of-sight hailing as well as digital hailing through a mobile app. Data from Columbus Yellow Cab were provided to the National Renewable Energy Laboratory to analyze the potential for taxi electrification. Columbus Yellow Cab data contained information describing both global positioning system trajectories and taxi meter information. The data spanned a period of 13 months, containing approximately 70 million global system positioning system points, 840 thousand trips, and 170 unique vehicles. A variety of scenarios were evaluated using Columbus Yellow Cab data and the Electric Vehicle Infrastructure Projection Tool (EVI-Pro) to understand challenges and opportunities associated with operating an electrified taxi fleet. Two main factors, access to home charging and vehicle specifications, are shown to be major variables affecting successful electric fleet operation. The analysis indicates that 95.7% of taxi travel days can be successfully completed by a 250-mile-range electric vehicle assuming access to overnight and public charging infrastructure. However, when no overnight access is available to fleet vehicles, only 39.9% of taxi travel days are possible with 250-mile range electric vehicles. An additional scenario, reducing the vehicle range from 250 miles to 100 miles (while controlling for infrastructure access and permitting overnight charging) resulted in only 34.4% of taxi travel days being completed.
This presentation summarizes some of the findings from the Electrification Futures Study.
In Athena ZEV, the next phase of the DOE-funded Athena Project, NREL is working with Dallas-Fort Worth International (DFW) airport and other partners to develop sophisticated strategies that will accelerate the decarbonization of millions of vehicles operating at and around airports. This work has an initial focus on the critical emerging challenge of rapid electrification of rental car operations and evaluating solutions through the NREL ARIES energy system simulation platform.
This one-page highlight details the key takeaways from a project that utilized NREL's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline, the Electrification Analysis of Container Ports' Cargo Handling Equipment project. This project created a scalable solution to model energy demand per shipping container moved (kWh/TEU) for an all-electric cargo handling equipment fleet located at a maritime port. The model allows stakeholders to understand energy demand at each electric vehicle (EV) equipment level and is easily scalable to container demand and EV adoption rate projections.
This one-page highlight details the key takeaways from a project that utilized NREL's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline. As part of the North American Council for Freight Efficiency's (NACFE's) Run on Less Depot data workshop, NREL sought to understand how Tesla semi-trucks would perform in real-world regional haul applications. Analysis reveals that the modeled Tesla trucks, with an average efficiency of 1.78 kWh/mi, struggle to achieve full operational coverage using current battery and charging configurations assuming operations remain unchanged. However, in an extreme case where ubiquitous charging exists, 100% EV coverage is possible for the given drive cycles. These findings highlight the trade-off between battery size and charge rate in electrification potential and emphasize the necessity for advancements in charging infrastructure to enable electric trucks for regional haul operations.
Given the explosive growth of the passenger vehicle market and energy demands in China, research on vehicle-use intensity and driver-travel patterns is critical for better assessing travel demand and its implications for alternative fuel vehicles, energy security, and environmental policies. This study attempts to estimate annual vehicle kilometers traveled (AVKT) per privately-owned passenger vehicle and their daily distance patterns by vehicle class and geographic region. The data sample from a survey consists of 169,292 privately owned passenger vehicles, made by 177 car manufacturers during 2003–2018, running in 82 cities from 27 provincial regions. The log-transformed average AVKT is estimated to be 12,377 km with 95% probability ranging from 5490 to 28,579 km. The investigation reveals that vehicles from South China have the highest AVKT at 13,320 km. Generally, vehicles in small cities have higher AVKT than in big cities, except AVKT of tier 1 cities being higher. Another trend is that more expensive or larger vehicles tend to be driven more. A model is fitted for estimating AVKT based on region, city type, automaker, price range, and certain vehicle features including class and age. Data of daily commuting distances in recent years are also analyzed. The average daily commuting distances typically range from 21 to 28 km. Using the validated Gamma distribution method, daily distance distributions are specified for different regions. It is found that 99% of the daily driving distance is no more than 88.0–112.0 km, depending on region. Utility factors of plug-in electric vehicles are also estimated to be much higher than those based on driving data in the USA. Finally, these findings suggest global mitigations strategies on vehicle fuel use, electrification, and greenhouse gases should consider vehicle-use intensity at the regional level.
The U.S. light-duty vehicle (LDV) industry, a major greenhouse gas (GHG) emitting sector, is embracing decarbonization. Considering only electrification pathways, this study uses publicly-available tools – MA3T and VISION on vehicle market penetration, fleet accounting and life-cycle analysis to quantify the policy gaps for LDVs to achieve the net-zero GHG emissions target in nine vehicle penetration cases under two electricity mix scenarios, including the U.S. administration's decarbonization strategy – 100% clean electricity by 2035. The MA3T model is a multinomial discrete choice model for market share projection by vehicle technology, and the VISION is a vehicle stocks and GHG emissions projection model by using vehicle and travel characteristics. This study projects the impacts of technology and policy enforcement on shaping the dynamics and decarbonization of the LDV market. Additionally, achieving the expected improvement of battery technology and charging infrastructure is critical but can only reduce the 2050 GHG emissions to 48–54% of the 2020 level under the electricity renewable mix scenario. It is almost impossible to achieve a 100% battery electric vehicle stock by 2050 and the 2050 net-zero target in the LDV industry unless ban of internal combustion engine technology is implemented starting in 2035 and under the 2035 100% clean electricity scenario. These extreme conditions also sacrifice most from the consumer welfare perspective. A greater policy forcing intensity accelerates plug-in electric vehicle penetration, while with declining marginal effect and reduced consumer welfare. Among the investigated policy scenarios, the policy forcing intensity equivalent to a fuel tax of $1–2 per gasoline gallon reduces the most GHG emissions while keeping a positive consumer welfare.
In this work, it is described how recently in the July 6, 2021 issue of Environmental Science & Technology, Tong et al. estimated health and climate impacts from large-scale long-haul truck electrification. The monetized damages range from a 47%–54% increase to a 77%–88% reduction. However, with adjustments to the marginal emission and static assumptions, impacts are found to be almost certainly positive, a 7%–94% reduction in damages.
As global electrification becomes more prominent, demand is projected to increase for electric vehicles (EVs), their components (EV batteries, rare earth traction motors), and their raw materials (cobalt, rare earths). To analyze the supply chain constraints associated with these components and raw materials, a system dynamics model was developed to simulate the interactions between the rare earth and cobalt supply chains. The results showed that under current understanding of raw material resources, production of the projected volume of EVs could be inadequate. To meet the aggressive EV volume sale projections set by the International Energy Agency, EV manufacturers will need to implement a large portion of traction motors without rare earths and utilize non-cobalt batteries as much as possible. On the supply side, a much faster ramp-up than what being modeled would be needed to meet much higher demand than current market forecasts.
Abstract Contact electrification, or contact charging, refers to the process of static charge accumulation after rubbing, or even simple touching, of two materials. Despite its relevance in static electricity, various natural phenomena, and numerous technologies, contact charging remains poorly understood. For insulating materials, even the species of charge carrier may be unknown, and the direction of charge-transfer lacks firm molecular-level explanation. Here, we use all-atom molecular dynamics simulations to investigate whether thermodynamics can explain contact charging between insulating polymers. Based on prior work suggesting that water-ions, such as hydronium and hydroxide ions, are potential charge carriers, we predict preferred directions of charge-transfer between polymer surfaces according to the free energy of water-ions within water droplets on such surfaces. Broad agreement between our predictions and experimental triboelectric series indicate that thermodynamically driven ion-transfer likely influences contact charging of polymers. Furthermore, simulation analyses reveal how specific interactions of water and water-ions proximate to the polymer-water interface explain observed trends. This study establishes relevance of thermodynamic driving forces in contact charging of insulators with new evidence informed by molecular-level interactions. These insights have direct implications for future mechanistic studies and applications of contact charging involving polymeric materials.
Major technological advancements and recent policy support are improving the outlook for heavy-duty truck electrification in the United States. In particular, short-haul operations (=200 miles (=322 km)) are prevalent and early candidates for plug-in electric vehicles (EVs) given their short, predictable routes and return-to-base applications, which allows vehicles to recharge when off shift at their depots. Although previous studies investigated the impacts of added electrical loads on distribution systems, which included light-duty EVs, the implications for heavy-duty EV charging are underexplored. Here we summarize the causes, costs and lead times of distribution system upgrades anticipated for depot charging. We also developed synthetic depot charging load profiles for heavy-duty trucks from real-world operating schedules, and found that charging requirements are met at common light-duty EV charging rates (=100 kW per vehicle). Finally, we applied depot charging load profiles to 36 distribution real-world substations, which showed that most can accommodate high levels of heavy-duty EV charging without upgrades.
Abstract Electrifying the transportation sector is crucial for reducing greenhouse gas emissions and offers numerous benefits including increased energy efficiency, lower total ownership costs, enhanced national energy security, and improved air quality. Despite the availability of necessary technologies, fully integrating the transportation and electricity sectors presents challenges in understanding all benefits and risks. Previous studies have not highlighted the role of coupling between these sectors. To better understand this coupling, this work reviews the structure of the current fossil-fuel-based transportation sector (including its dependence on the electricity sector) and case studies of its vulnerabilities to key risks. By adopting a systemic perspective, we uncover the indispensable interplay between the transportation and electricity sectors, shedding light on previously neglected dynamics. Leveraging the principles of grid architecture (GA), we introduce a hierarchical approach to assess vulnerabilities within the prevailing fuel-based transportation system and elucidate pathways for enhancement through electrification.