The study has characterized the magnitude and the range of possible emissions impacts as compared to multiple baselines . A clear message that emerges is that decision-makers must avail themselves of better foresight and informed decision-making on near-term and longer-term timescales. More comprehensive awareness of vehicle use cases, and energy needs in time and space will help small businesses and utilities predict and plan for EV charging events. This research suggests that when marginal emissions can be at or below the weighted average values, environmental benefits stand to be greater. A unique attribute of this study compared to prior efforts is that its scope speaks more directly to small business owners and vehicle fleet operators. These stakeholder groups and their associated applications are known to realize a few advantages in comparison with individual vehicle owners driving LDVs. The reason is that the selected categories of service vehicles largely return to a central base and navigate similar, standardized routes on a recurring basis. They also travel sufficient but not overly excessive distances: a factor that may help approach the Goldilocks state. Finally, and perhaps not coincidentally, this audience seems to be targeted by automakers of late, given a limited growing number of new EV models entering the market. Though both LDV and MD use cases have societal implications involving decisions around the generation mix and utility infrastructure, it is the potential to leverage an EV to save money that could pull the technology quickly ahead and spur scale up in other vehicle sectors. The study has implications for policy and public investment, cannabis drying including an even more urgent need for managed and coordinated charging, and greater attention to resource planning.

This is especially relevant for infrastructure funding, for which the Federal Government has deployed upwards of $7.5B to states and set a goal to realize 500,000 chargers by the year 2030. The report concludes with a few suggestions for future work, including the need to leverage this methodology to quantify the monetized value of CO2 emissions in conjunction with other investment costs for capital and operations. Finally, the research team believes the model has relevance and can be scaled and adapted for conducting similar analyses in other regions.In short, it is imperative to not only manage EV charging events in time and space, but also consider our latitude to control or influence other large loads on the grid in conjunction with EV deployment growth. This study reveals that several Medium and Heavy-Duty EV use cases can offer significant benefits, but also makes it clear that decisions around charging operations, infrastructure and grid support must be conducted at a system level that considers vehicles, their use cases, as well as the temporal nature of grid generation. In this way, the electrification of transportation is more likely to result in measurable decarbonization gains, substantive environmental and health benefits, and reasonable returns on investment.Vehicle electrification not only continues to garner momentum, but also public and private funding, and is considered a viable means of growing the national economy and decarbonizing major segments of the transportation sector. A growing body of evidence demonstrates that substitution of gasoline-consuming vehicles with electrified alternatives eliminates tailpipe emissions contributing to reductions in CO2 emissions as well as in criteria pollutants. Whereas CO2 reductions can favorably affect global climate change trends, pollutant emissions reductions can improve urban air quality on a more local scale, and by extension improve public health.

A key advantage of Electric Vehicles compared to internal combustion engine vehicles is that their carbon and emissions footprint is not fixed based on the vehicle technology from a given past model year, but instead can progressively improve in lock step with a grid that is evolving toward a cleaner and lower carbon generating mix. Driven in part by policy, declining prices, and product availability, EV deployments are accelerating, having surpassed 2,000,000 vehicles sold in the U.S. fleet by Dec 2022. Though EVs still account for less than 1% of the domestic vehicle fleet, the growth is definitely accelerating. Projections for continued EV growth through the present “second decade” of mass deployment are varied, and uncertainty is a factor for both capital costs and energy costs. Still, many sources suggest sustained growth approaching double digit shares of the fleet by 2030. EVs are increasingly seen as a win-win solution by many policymakers, in that they can provide benefits to consumers, automakers, and utilities, while also reducing environmental impacts. In spite of substantial progress and aggressive policy support, non-trivial barriers remain. These barriers may simultaneously threaten both broader adoption and certain beneficial outcomes of EV growth. Among one the most critical and poorly understood, is the need to ensure environmental benefits live up to their promise as deployments exceed 10% of the future fleet. This seems to be a kind of threshold of market penetration beyond which grid capacity, resource adequacy, broader electrification, levelized energy costs, and decarbonization may be challenged. While much public attention is focused on light duty vehicle markets , significant opportunities are believed to exist in Medium Duty and certain Heavy Duty applications. For this reason, the EVALUATE research team has conducted a twoyear, two-phase research investigation focused on methodologies and applications across major Light Duty and Medium Duty vehicle classifications. Key contributions of our Phase I included the development of a rigorous methodology involving a high-fidelity system of systems model.

This included a sub-system model for vehicle power trains which provide accurate estimates of energy consumption for representative driving cycles. Additionally, it included a literature review, survey data, observed experimental data, and a protocol to inform EV charging profiles. And finally, it included a series of datasets and procedures developed to understand how electric power is dispatched and delivered at the bulk grid level. More specifically, it generated a high-resolution characterization of the emission rates associated with electric power generation on an hourly, daily, seasonal, and annual basis. While studies have explored each of these sub-systems independently, the research team has been among the first to develop them in an integrated manner to forecast the emissions outputs of a class of vehicles and a range of use cases. The phase I findings were significant and explored light-duty vehicles through typical urban commuters and households that operate LDVs for daily personal use. [See Phase I final report for more on the initial study and its key findings, 1].The over-arching goal of the EVALUATE project has been to ensure that reductions in CO2 and pollutant emissions are more fully understood, and that decision-makers have guidance and tools to help realize them. The research team believes this will be imperative as EV market penetration scales up . To achieve this goal, Phase I of this project developed a system of integrated vehicle, transportation, and electric power system models designed to evaluate hourly marginal CO2 emissions rates for a regional study under various demand scenarios between now and 2030. As noted, the focus was on personal vehicles in the light-duty category. Phase II of this project, presented here, demonstrates the usefulness of these tools in providing policy-relevant information to practitioners and decision-makers. As such, we focus on a series of targeted case studies that extend prior work from LDVs operated by individuals to service oriented vehicles operated by small and medium businesses.To augment the analysis and build upon prior work, additional inquiries were made into the type and capacity of EV charging devices that would be required for these larger vehicles and different use cases. For instance, Phase II has focused more extensively on medium rate and fast charging methods1 . In conjunction, the research team assessed likely charging behavior that would be typical of small businesses in the subject categories. Again, the goal has been to better understand how vehicle use case, charging behavior, and assumptions around the grid, with a particular focus on marginal emissions, may affect the environmental impacts and other relative pros and cons of EVs as a substitute for the incumbent vehicle technology . The selected scenarios and simulated outputs are based upon a series of case studies in the Atlanta, Georgia metropolitan area using local assumptions along with historical and projected grid data for Georgia Power and the Southern Company balancing authority. These case studies evaluate the influence of vehicle classification, usage, best way to dry bud and charging strategies for EVs in both light-duty vehicles and medium-duty trucks .

All case studies explore the relationship between the selected scenarios and the resulting carbon intensity of marginal electrical power generation. This investigation provides an important theoretical contribution to our overall understanding of vehicle electrification for intermediate market penetration rates. Equally important, the study demonstrates the ability of the EVALUATE modeling system to produce practical policy-relevant findings that are valuable to stakeholders that relate to our selected scenarios, the Southeast region, and more broadly. This research is uniquely positioned to address critical gaps and inform strategic decisions that will be economically viable and favorably advance EVs, sustainable transportation solutions, and their concomitant policies. This research identified representative use cases that included Light and Medium Duty return-to-base fleets. Prior to the present study, the research team oversaw a Georgia Tech student-led effort that conducted a preliminary techno-economic investigation into residential service vehicles such as those used by HVAC, exterminator, plumbing, and landscaping personnel, with some high-level economic indicators depicted in Fig 1-1. To this, the current research team added new business-related scenarios including ecommerce, package delivery vehicles, moving trucks, and refuse trucks. In the present study, the team applies the marginal emissions methodology to these expanded use cases, to further demonstrate how the methodology can be applied, and yield some illustrative insights for several discrete vehicle categories and use case scenarios. Finally, the study provides guidance that can inform how decision-makers can optimize effectiveness and cost based on the team’s approach .This research requires the synthesis of three independent sub-system models and data developed or identified by the research team in the areas of vehicle propulsion and auxiliary power and energy need to satisfy prescribed trip/travel demands for a range of vehicle technologies and applications, EV charging profiles that would be considered typical for the service, fleet and medium duty vehicle use cases, and grid generation dispatch with commensurate consideration of emissions intensities for CO2 and major criteria pollutants. The team has extensive experience developing high-fidelity sub-system models and applying them to both generalizable and regional scenarios. As an input to the two phases of the EVALUATE project, the team drew upon more than three years of prior efforts acquiring and conditioning open-source data, alternative vehicle architectures, customized datasets for regional electric power dispatch , and numerous travel route pathways. Under the EVALUATE project, the team deepened its experience by integrating several of these subsystem resources into a holistic picture of emissions by vehicle type and use case. The scope of the second phase of this project has been to update and develop new, more accurate subsystem models and datasets that are granular and of specific relevance to service fleets and medium-duty vehicle operators. The end result of the two phases, therefore, is a set of integrated models built upon high-fidelity data from real-world use cases that generate a range of simulations. Throughout the EVALUATE project, the simulations are generated primarily to draw comparisons, understand the impact of fundamental assumptions around charging behavior and grid emissions, and develop initial guidance around the relative merits of EVs under representative use cases. The use of these tools to guide private sector fleets and medium-duty vehicle operators can be timely since few high-fidelity emissions calculators are available to accompany proprietary economic assessment tools.The team’s methodology was developed in Phase I and expanded in Phase II for the purpose of investigating a broader set of vehicles and charging profiles that typify urban service fleet and medium-duty delivery applications. A brief recap of the major steps in the analysis is presented here. First, physics-based vehicle energy consumption models are developed which facilitate comparisons among vehicle architectures that utilize energy from disparate primary sources . As noted, the Phase II effort extended the modeling from light-duty cars used for personal use, to light-duty pickup trucks and vans used for serviceoriented businesses. Additional models were derived and corroborated against background data to characterize medium-duty delivery trucks and a heavy-duty urban application . A related task involved the identification of driving cycles that approximate typical routes traveled by the associated vehicles.