Impact of electric vehicle charging demand on power distribution grid congestion.

California, a pioneer in EV adoption, has enacted ambitious electric vehicle (EV) policies that will generate a large burden on the state's electric distribution system. We investigate the statewide impact of uncontrolled EV charging on the electric distribution networks at a large scale and high granularity, by employing an EV charging profile projection that combines travel demand model, EV adoption model, and real-world EV charging data. We find a substantial need for infrastructure upgrades in 50% of feeders by 2035, and 67% of feeders by 2045. The distribution system across California must upgrade its capacity by 25 GW by 2045, corresponding to a cost between $6 and $20 billion. While the additional infrastructure cost drives the electricity price up, it is offset by the downward pressure from the growth of total electricity consumption and leads to a reduction in electricity rate between $0.01 and $0.06/kWh by 2045. We also find that overloading conditions are highly diverse spatially, with feeders in residential areas requiring twice as much upgrade compared to commercial areas. Our study provides a framework for evaluating EVs' impact on the distribution grid and indicates the potential to reduce infrastructure upgrade costs by shifting home-charging demand. The imminent challenges confronting California serve as a microcosm of the forthcoming obstacles anticipated worldwide due to the prevailing global trend of EV adoption.

What Do We Know about Zero-Emission Vehicle Mandates?

Many researchers, policymakers, and stakeholders view zero-emissions vehicles (ZEVs) as playing an important role in deep decarbonization of the transport sector. Here, we bring attention to one policy that can effectively induce ZEV sales in the long term: a ZEV sales mandate. Although three decades have passed since the first mandate was implemented in California, there is surprisingly little research regarding its policy impacts. From a greenhouse gas (GHG) mitigation perspective, we argue that ZEV mandates should be framed and analyzed as complex policy-with intended impacts on industry, consumers, and institutions over the long term. We present an interdisciplinary framework to address this complexity, summarizing the limited evidence to date on policy effectiveness, efficiency, public acceptability, and transformative potential. We conclude with a critical research agenda to improve understanding of the role of a mandate in an effective policy mix.

Energy, Emissions, and Cost Impacts of Charging Price Strategies for Electric Vehicles.

While utilizing price signals to affect charging behaviors has been identified as a promising strategy to manage charging loads, few studies discuss their impacts comprehensively. We investigate how different charging price strategies can affect the spatial and temporal distribution of charging activities at the individual level and the required charging infrastructure system. We utilize an integrated optimization platform for electric vehicle (EV) charging management and infrastructure placement in home and nonhome locations in San Diego, CA, that include charging price strategies, infrastructure costs, and mobility demand patterns. We evaluate three pricing scenarios and demonstrate that the time-of-use pricing scheme results in the highest emissions and the real-time one the lowest, which are 20.2% higher and 0.7% lower than the annual emissions under the flat rate scenario, which is about 8,787 MtCO2e. Our results show that the charging load profile is the result of various determinants including the dynamic electricity price, price elasticity of charging demand, travel and dwelling constraints, carbon price, as well as exclusive home and shared nonhome charging patterns. The effectiveness of changing charging behavior through internalizing climate damage to obtain environmental benefits depends largely on charging price strategies, implying that policymakers should consider charging price strategies in conjunction with carbon pricing rather than independently.

Distribution grid impacts of electric vehicles: A California case study.

California has adopted a substantial number of electric vehicles over the last decade but there are many challenges associated with the electrification of vehicles, including how they interact with the electricity grid. We employ real-world feeder circuit level data in California from PG&E to measure the capacity of local feeders. We model the adoption of electric vehicles down to the census block and take advantage of real-world vehicle charging data to simulate the future loading on circuits throughout Northern California. In our highest adoption scenario of 6 million electric vehicles in California, we find that across PG&E's service territory, 443 circuits will require upgrades (nearly 20% of all circuits) and merely 88 of these feeders have planned upgrades in the future. The costs of these feeders are an essential part of a utility's planning process, and this work speaks to the importance of electric vehicles on local distribution networks.

Health and Climate Impacts from Long-Haul Truck Electrification.

Long-haul truck electrification has attracted nascent policy support, but the potential health and climate impacts remain uncertain. Here, we developed an integrated assessment approach with high spatial-temporal (km and hourly) resolution to characterize the causal chain from truck operation to charging loads, electricity grid response, changes in emissions and atmospheric concentrations, and the resulting health and climate impacts across the United States. Compared to future diesel trucks, electrified trucking's net health benefits are concentrated only along the West Coast with a business-as-usual electricity grid. However, with an 80%-renewable electricity grid, most regions would experience net health benefits, and the economic value of avoided climate and health damages exceeds $5 billion annually, an 80% reduction relative to future diesel trucks. Electric trucks with larger batteries may increase health and climate impacts due to additional trips needed to compensate for the payload penalty, but a 2× improvement in the battery specific energy (to ∼320 Wh/kg) could eliminate the additional trips.

Private versus Shared, Automated Electric Vehicles for U.S. Personal Mobility: Energy Use, Greenhouse Gas Emissions, Grid Integration, and Cost Impacts.

Transportation is the fastest-growing source of greenhouse gas (GHG) emissions and energy consumption globally. While the convergence of shared mobility, vehicle automation, and electrification has the potential to drastically reduce transportation impacts, it requires careful integration with rapidly evolving electricity systems. Here, we examine these interactions using a U.S.-wide simulation framework encompassing private electric vehicles (EVs), shared automated EVs (SAEVs), charging infrastructure, controlled EV charging, and a grid economic dispatch model to simulate personal mobility exclusively using EVs. We find that private EVs with uncontrolled charging would reduce GHG emissions by 46% compared to gasoline vehicles. Private EVs with fleetwide controlled charging would achieve a 49% reduction in emissions from baseline and reduce peak charging demand by 53% from the uncontrolled scenario. We also find that an SAEV fleet 9% the size of today's active vehicle fleet can satisfy trip demand with only 2.6 million chargers (0.2 per EV). Such an SAEV fleet would achieve a 70% reduction in GHG emissions at 41% of the lifecycle cost as a private EV fleet with controlled charging. The emissions and cost advantage of SAEVs is primarily due to reduced vehicle manufacturing compared with private EVs.

Cost Implications for Automaker Compliance of Zero Emissions Vehicle Requirements.

While there are many automotive regulations in the United States, few studies in the literature examine the interaction between different rules. We investigate the cost implications of enforcing the national Corporate Average Fuel Economy (CAFE) and greenhouse gas (GHG) emissions standards and the Zero Emissions Vehicle (ZEV) requirements simultaneously. We construct a new "Cost Optimization Modeling for Efficiency Technologies" (COMET) to understand how vehicle manufacturers implement fuel economy technologies to comply with multiple regulations. We consider a variety of scenarios to measure the interaction between regulations and how they may lead to changes in technology costs. In 2025, unit costs reach $1,600 per vehicle on average to comply with CAFE/GHG and increase to $2,000 per vehicle on average to comply with both CAFE/GHG and ZEV. Unit costs for both regulations are less than the sum of the two because vehicles produced to comply with the ZEV program count toward compliance with the CAFE.

Alternative Fuel Vehicle Adoption Increases Fleet Gasoline Consumption and Greenhouse Gas Emissions under United States Corporate Average Fuel Economy Policy and Greenhouse Gas Emissions Standards.

The United States Corporate Average Fuel Economy (CAFE) standards and Greenhouse Gas (GHG) Emission standards are designed to reduce petroleum consumption and GHG emissions from light-duty passenger vehicles. They do so by requiring automakers to meet aggregate criteria for fleet fuel efficiency and carbon dioxide (CO2) emission rates. Several incentives for manufacturers to sell alternative fuel vehicles (AFVs) have been introduced in recent updates of CAFE/GHG policy for vehicles sold from 2012 through 2025 to help encourage a fleet technology transition. These incentives allow automakers that sell AFVs to meet less-stringent fleet efficiency targets, resulting in increased fleet-wide gasoline consumption and emissions. We derive a closed-form expression to quantify these effects. We find that each time an AFV is sold in place of a conventional vehicle, fleet emissions increase by 0 to 60 t of CO2 and gasoline consumption increases by 0 to 7000 gallons (26,000 L), depending on the AFV and year of sale. Using projections for vehicles sold from 2012 to 2025 from the Energy Information Administration, we estimate that the CAFE/GHG AFV incentives lead to a cumulative increase of 30 to 70 million metric tons of CO2 and 3 to 8 billion gallons (11 to 30 billion liters) of gasoline consumed over the vehicles' lifetimes - the largest share of which is due to legacy GHG flex-fuel vehicle credits that expire in 2016. These effects may be 30-40% larger in practice than we estimate here due to optimistic laboratory vehicle efficiency tests used in policy compliance calculations.

A subpopulation of macrophages infiltrates hypertrophic adipose tissue and is activated by free fatty acids via Toll-like receptors 2 and 4 and JNK-dependent pathways.

Obesity and type 2 diabetes are characterized by decreased insulin sensitivity, elevated concentrations of free fatty acids (FFAs), and increased macrophage infiltration in adipose tissue (AT). Here, we show that FFAs can cause activation of RAW264.7 cells primarily via the JNK signaling cascade and that TLR2 and TLR4 are upstream of JNK and help transduce FFA proinflammatory signals. We also demonstrate that F4/80(+)CD11b(+)CD11c(+) bone marrow-derived dendritic cells (BMDCs) have heightened proinflammatory activity compared with F4/80(+)CD11b(+)CD11c(-) bone marrow-derived macrophages and that the proinflammatory activity and JNK phosphorylation of BMDCs, but not bone marrow-derived macrophages, was further increased by FFA treatment. F4/80(+)CD11b(+)CD11c(+) cells were found in AT, and the proportion and number of these cells in AT is increased in ob/ob mice and by feeding wild type mice a high fat diet for 1 and 12 weeks. AT F4/80(+)CD11b(+)CD11c(+) cells express increased inflammatory markers compared with F4/80(+)CD11b(+)CD11c(-) cells, and FFA treatment increased inflammatory responses in these cells. In addition, we found that CD11c expression is increased in skeletal muscle of high fat diet-fed mice and that conditioned medium from FFA-treated wild type BMDCs, but not TLR2/4 DKO BMDCs, can induce insulin resistance in L6 myotubes. Together our results show that FFAs can activate CD11c(+) myeloid proinflammatory cells via TLR2/4 and JNK signaling pathways, thereby promoting inflammation and subsequent cellular insulin resistance.