Plug-in hybrid vehicle GHG impacts in California: Integrating consumer-informed recharge profiles with an electricity-dispatch model

This paper explores how Plug-in Hybrid Vehicles (PHEVs) may reduce source-to-wheel Greenhouse Gas (GHG) emissions from passenger vehicles. The two primary advances are the incorporation of (1) explicit measures of consumer interest in and potential use of different types of PHEVs and (2) a model of the California electricity grid capable of differentiating hourly and seasonal GHG emissions by generation source. We construct PHEV emissions scenarios to address inherent relationships between vehicle design, driving and recharging behaviors, seasonal and time-of-day variation in GHG-intensity of electricity, and total GHG emissions. A sample of 877 California new vehicle buyers provide data on driving, time of day recharge access, and PHEV design interests. The elicited data differ substantially from the assumptions used in previous analyses. We construct electricity demand profiles scaled to one million PHEVs and input them into an hourly California electricity supply model to simulate GHG emissions. Compared to conventional vehicles, consumer-designed PHEVs cut marginal (incremental) GHG emissions by more than one-third in current California energy scenarios and by one-quarter in future energy scenarios—reductions similar to those simulated for all-electric PHEV designs. Across the emissions scenarios, long-term GHG reductions depends on reducing the carbon intensity of the grid.     

Plug-in hybrid electric vehicle charge pattern optimization for energy cost and battery longevity

This paper examines the problem of optimizing the charge pattern of a plug-in hybrid electric vehicle (PHEV), defined as the timing and rate with which the PHEV obtains electricity from the power grid. The optimization goal is to simultaneously minimize (i) the total cost of fuel and electricity and (ii) the total battery health degradation over a 24-h naturalistic drive cycle. The first objective is calculated for a previously-developed stochastic optimal PHEV power management strategy, whereas the second objective is evaluated through an electrochemistry-based model of anode-side resistive film formation in lithium-ion batteries. The paper shows that these two objectives are conflicting, and trades them off using a non-dominated sorting genetic algorithm. As a result, a Pareto front of optimal charge patterns is obtained. The effects of electricity price and trip schedule on the optimal Pareto points and the PHEV charge patterns are analyzed and discussed.     

Fuel reduction and electricity consumption impact of different charging scenarios for plug-in hybrid electric vehicles

Plug-in hybrid electric vehicles (PHEVs) consume both gasoline and grid electricity. The corresponding temporal energy consumption and emission trends are valuable to investigate in order to fully understand the environmental benefits. The 24-h energy consumption and emission profile depends on different vehicle designs, driving, and charging scenarios. This study assesses the potential energy impact of PHEVs by considering different charging scenarios defined by different charging power levels, locations, and charging time. The region selected for the study is the South Coast Air Basin of California. Driving behaviors are derived from the National Household Travel Survey 2009 (NHTS 2009) and vehicle parameters are based on realistic assumptions consistent with projected vehicle deployments. Results show that the reduction in petroleum consumption is significant compared to standard gasoline vehicles and the ability to operate on electricity alone is crucial to cold start emission reduction. The benefit of higher power charging on petroleum consumption is small. Delayed and average charging are better than immediate charging for home, and non-home charging increases peak grid loads.     

Plug-in hybrid electric vehicles can be clean and economical in dirty power systems

Plug-in hybrid electric vehicles (PHEVs) that are driven and charged in ‘dirty’ power systems, with high penetrations of coal and other polluting generation fuels, may yield higher net emissions than conventional vehicles (CVs). We examine the implications of imposing a constraint on PHEV recharging that forces emissions from PHEVs to be no greater than those from a comparable CV. We use the Texas power system, which has a mix of coal- and natural gas-fired generation and has been shown to yield higher emissions from PHEVs than CVs, as a case study. Our results show that imposing the emissions constraint results in most of the PHEV charging loads being shifted from coal- to cleaner natural gas-fired generators. There is, however, virtually no increase in generation or PHEV driving costs due to efficiency benefits that are possible through coordination of unit commitment and PHEV charging decisions.     

Targeting plug-in hybrid electric vehicle policies to increase social benefits

In 2009 the U.S. federal government enacted tax credits aimed at encouraging consumers to purchase plug-in hybrid electric vehicles (PHEVs). These tax credits are available to all consumers equally and therefore do not account for the variability in social benefits associated with PHEV operation in different parts of the country. The tax credits also do not consider variability in consumer income. This paper discusses why the PHEV subsidy policy would have higher social benefits at equal or less cost if the tax credits were offered at different levels depending on consumer income and the location of purchase. Quantification of these higher social benefits and related policy proposals are left for future work.     

Advanced vehicles: Costs, energy use, and macroeconomic impacts

Advanced vehicles and alternative fuels could play an important role in reducing oil use and changing the economy structure. We developed the Costs for Advanced Vehicles and Energy (CAVE) model to investigate a vehicle portfolio scenario in California during 2010-2030. Then we employed a computable general equilibrium model to estimate macroeconomic impacts of the advanced vehicle scenario on the economy of California. Results indicate that, due to slow fleet turnover, conventional vehicles are expected to continue to dominate the on-road fleet and gasoline is the major transportation fuel over the next two decades. However, alternative fuels could play an increasingly important role in gasoline displacement. Advanced vehicle costs are expected to decrease dramatically with production volume and technological progress; e.g., incremental costs for fuel cell vehicles and hydrogen could break even with gasoline savings in 2028. Overall, the vehicle portfolio scenario is estimated to have a slightly negative influence on California's economy, because advanced vehicles are very costly and, therefore, the resulting gasoline savings generally cannot offset the high incremental expenditure on vehicles and alternative fuels. Sensitivity analysis shows that an increase in gasoline price or a drop in alternative fuel prices could offset a portion of the negative impact.     

Emissions impacts of plug-in hybrid electric vehicle deployment on the U.S. western grid

The constantly evolving western grid of the United States is characterized by complex generation dispatch based on economics, contractual agreements, and regulations. The future electrification of transportation via plug-in electric vehicles calls for an energy and emissions analysis of electric vehicle (EV) penetration scenarios based on realistic resource dispatch. A resource dispatch and emissions model for the western grid is developed and a baseline case is modeled. Results are compared with recorded data to validate the model and provide confidence in the analysis of EV-grid interaction outlooks. A modeled dispatch approach, based on a correlation between actual historical dispatch and system load data, is exercised to show the impacts (emission intensity, temporally resolved load demand) associated with EV penetration on the western grid. The plug-in hybrid electric vehicle (PHEV) and selected charging scenarios are the focus for the analysis. The results reveal that (1) a correlation between system load and resource group capacity factor can be utilized in dispatch modeling, (2) the hourly emissions intensity of the grid depends upon PHEV fleet charge scenario, (3) emissions can be reduced for some species depending on the PHEV fleet charge scenario, and (4) the hourly model resolution of changes in grid emissions intensity can be used to decide on preferred fleet-wide charge profiles.     

Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power

This paper uses a new unit commitment model which can simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). Four PHEV charging scenarios are simulated for the Illinois power system: (1) unconstrained charging, (2) 3-hour delayed constrained charging, (3) smart charging, and (4) smart charging with DR. The PHEV charging is assumed to be optimally controlled by the system operator in the latter two scenarios, along with load shifting and shaving enabled by DR programs. The simulation results show that optimally dispatching the PHEV charging load can significantly reduce the total operating cost of the system. With DR programs in place, the operating cost can be further reduced.     

Analysis of plug-in hybrid electric vehicle utility factors

Plug-in hybrid electric vehicles (PHEVs) are hybrid electric vehicles that can be fueled from both conventional liquid fuels and grid electricity. To represent the total contribution of both of these fuels to the operation, energy use, and environmental impacts of PHEVs, researchers have developed the concept of the utility factor. As standardized in documents such as SAE J1711 and SAE J2841, the utility factor represents the proportion of vehicle distance travelled that can be allocated to a vehicle test condition so as to represent the real-world driving habits of a vehicle fleet. These standards must be used with care so that the results are understood within the context of the assumptions implicit in the standardized utility factors. This study analyzes and derives alternatives to the standard utility factors from the 2001 National Highway Transportation Survey, so as to understand the sensitivity of PHEV performance to assumptions regarding charging frequency, vehicle characteristics, driver characteristics, and means of defining the utility factor. Through analysis of these alternative utility factors, this study identifies areas where analysis, design, and policy development for PHEVs can be improved by alternative utility factor calculations.     

Influence of driving patterns on life cycle cost and emissions of hybrid and plug-in electric vehicle powertrains

We compare the potential of hybrid, extended-range plug-in hybrid, and battery electric vehicles to reduce lifetime cost and life cycle greenhouse gas emissions under various scenarios and simulated driving conditions. We find that driving conditions affect economic and environmental benefits of electrified vehicles substantially: Under the urban NYC driving cycle, hybrid and plug-in vehicles can cut life cycle emissions by 60% and reduce costs up to 20% relative to conventional vehicles (CVs). In contrast, under highway test conditions (HWFET) electrified vehicles offer marginal emissions reductions at higher costs. NYC conditions with frequent stops triple life cycle emissions and increase costs of conventional vehicles by 30%, while aggressive driving (US06) reduces the all-electric range of plug-in vehicles by up to 45% compared to milder test cycles (like HWFET). Vehicle window stickers, fuel economy standards, and life cycle studies using average lab-test vehicle efficiency estimates are therefore incomplete: (1) driver heterogeneity matters, and efforts to encourage adoption of hybrid and plug-in vehicles will have greater impact if targeted to urban drivers vs. highway drivers; and (2) electrified vehicles perform better on some drive cycles than others, so non-representative tests can bias consumer perception and regulation of alternative technologies. We discuss policy implications.     

Modelling the impacts of electric vehicle recharging on the Western Australian electricity supply system

This study investigates the potential impacts of EVs on the Western Australian electricity grid, the constraints on the system’s capacity to supply electricity for EV recharging and the options for managing those potential impacts and constraints. Western Australia is geographically isolated and the electricity network has no interconnection with neighbouring regions. The State energy and vehicle markets are independent of issues occurring in neighbouring states. Western Australia is a relatively clean sample space. This study eliminates uncertainty in vehicle adoption rates from analysis by assuming that all new vehicles are EVs. This gives a worst case scenario in terms of load growth and shows that it will over 200,000 EVs, which represents 10% of the fleet, before there is any significant impact on peak demand even if charging behaviours are left unfettered. The study also shows, however, that the electricity supply and transmission industry can achieve significant short- and long-term benefits if vehicle charging behaviours are managed from the outset, through, for example, demand management or structured tariffs. In the short-term, providing incentive for off-peak recharging increases utilisation of existing transmission capacity, and cheaper, more efficient base-load generation infrastructure. In the long-term, investment in more underutilised capacity can be avoided.     

Integration of plug-in hybrid electric vehicles in a regional wind-thermal power system

This study investigates consequences of integrating plug-in hybrid electric vehicles (PHEVs) in a wind-thermal power system supplied by one quarter of wind power and three quarters of thermal generation. Four different PHEV integration strategies, with different impacts on the total electric load profile, have been investigated. The study shows that PHEVs can reduce the CO₂-emissions from the power system if actively integrated, whereas a passive approach to PHEV integration (i.e. letting people charge the car at will) is likely to result in an increase in emissions compared to a power system without PHEV load. The reduction in emissions under active PHEV integration strategies is due to a reduction in emissions related to thermal plant start-ups and part load operation. Emissions of the power sector are reduced with up to 4.7% compared to a system without PHEVs, according to the simulations. Allocating this emission reduction to the PHEV electricity consumption only, and assuming that the vehicles in electric mode is about 3 times as energy efficient as standard gasoline operation, total emissions from PHEVs would be less than half the emissions of a standard car, when running in electric mode.     

An agent-based model to study market penetration of plug-in hybrid electric vehicles

A spatially explicit agent-based vehicle consumer choice model is developed to explore sensitivities and nonlinear interactions between various potential influences on plug-in hybrid vehicle (PHEV) market penetration. The model accounts for spatial and social effects (including threshold effects, homophily, and conformity) and media influences. Preliminary simulations demonstrate how such a model could be used to identify nonlinear interactions among potential leverage points, inform policies affecting PHEV market penetration, and help identify future data collection necessary to more accurately model the system. We examine sensitivity of the model to gasoline prices, to accuracy in estimation of fuel costs, to agent willingness to adopt the PHEV technology, to PHEV purchase price and rebates, to PHEV battery range, and to heuristic values related to gasoline usage. Our simulations indicate that PHEV market penetration could be enhanced significantly by providing consumers with ready estimates of expected lifetime fuel costs associated with different vehicles (e.g., on vehicle stickers), and that increases in gasoline prices could nonlinearly magnify the impact on fleet efficiency. We also infer that a potential synergy from a gasoline tax with proceeds is used to fund research into longer-range lower-cost PHEV batteries.     

Market penetration analysis of electric vehicles in the German passenger car market towards 2030

There is currently intensive public discussion of fuel cell electric vehicles (FCEV) and other electric powertrains, such as battery electric vehicles (BEV), plug-in hybrid electric vehicles (PHEV) and hybridized combustion engine vehicles (HEV). In this context, the German government has set the target of one million electric vehicles on the road by 2020, and six million by 2030 [1]. The goal of this paper is to identify the possible market share of electric vehicles in the German new car fleet in three scenarios in the timeframe from 2010 to 2030. The VECTOR21 vehicle technology scenario model is used to model the fleet in three scenarios. In the reference scenario with business-as-usual parameters, 189,000 electric vehicles will be sold in Germany by 2020. Scenario two with purchase price incentives from 5000 EUR, high oil prices, and low prices for hydrogen and electricity will result in 727,000 vehicles. In the last scenario with substantial OEM mark-up reductions and external conditions as in the business-as-usual scenario, 3.28 million vehicles will be sold.     

A seasonal hybrid procedure for electricity demand forecasting in China

Electricity is a special energy which is hard to store, so the electricity demand forecasting in China remains an important problem. This paper aims at developing an improved hybrid model for electricity demand in China, which takes the advantages of moving average procedure, combined method, hybrid model and adaptive particle swarm optimization algorithm, known as MA-C-WH. It is designed for making trend and seasonal adjustments which simultaneously presents the electricity demand forecasts. Four actual electricity demand time series in China power grids are selected to illustrate the proposed MA-C-WH model, and one existing seasonal autoregressive integrated moving average model (SARIMA) is selected to compare with the proposed model using the same data series. The results of popular forecasting precision indexes show that our proposed model is an effective forecasting technique for seasonal time series with nonlinear trend.     

On the aggregate grid load imposed by battery health-conscious charging of plug-in hybrid electric vehicles

This article examines the problem of estimating the aggregate load imposed on the power grid by the battery health-conscious charging of plug-in hybrid electric vehicles (PHEVs). The article begins by generating a set of representative daily trips using (i) the National Household Travel Survey (NHTS) and (ii) a Markov chain model of both federal and naturalistic drive cycles. A multi-objective optimizer then uses each of these trips, together with PHEV powertrain and battery degradation models, to optimize both PHEV daily energy cost and battery degradation. The optimizer achieves this by varying (i) the amounts of charge obtained from the grid by each PHEV, and (ii) the timing of this charging. The article finally computes aggregate PHEV power demand by accumulating the charge patterns optimized for individual PHEV trips. The results of this aggregation process show a peak PHEV load in the early morning (between 5.00 and 6.00 a.m.), with approximately half of all PHEVs charging simultaneously. The ability to charge at work introduces smaller additional peaks in the aggregate load pattern. The article concludes by exploring the sensitivity of these results to the relative weighting of the two optimization objectives (energy cost and battery health), battery size, and electricity price.     

Hybrid and plug-in hybrid electric vehicle performance testing by the US Department of Energy Advanced Vehicle Testing Activity

The Advanced Vehicle Testing Activity (AVTA), part of the U.S. Department of Energy's FreedomCAR and Vehicle Technologies Program, has conducted testing of advanced technology vehicles since August 1995 in support of the AVTA goal to provide benchmark data for technology modeling, and vehicle development programs. The AVTA has tested full size electric vehicles, urban electric vehicles, neighborhood electric vehicles, and hydrogen internal combustion engine powered vehicles. Currently, the AVTA is conducting baseline performance, battery benchmark and fleet tests of hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV). Testing has included all HEVs produced by major automotive manufacturers and spans over 2.5 million test miles. Testing is currently incorporating PHEVs from four different vehicle converters. The results of all testing are posted on the AVTA web page maintained by the Idaho National Laboratory.     

Impact of battery weight and charging patterns on the economic and environmental benefits of plug-in hybrid vehicles

Plug-in hybrid electric vehicle (PHEV) technology is receiving attention as an approach to reducing US dependency on foreign oil and greenhouse gas (GHG) emissions from the transportation sector. PHEVs require large batteries for energy storage, which affect vehicle cost, weight, and performance. We construct PHEV simulation models to account for the effects of additional batteries on fuel consumption, cost, and GHG emissions over a range of charging frequencies (distance traveled between charges). We find that when charged frequently, every 20 miles or less, using average US electricity, small-capacity PHEVs are less expensive and release fewer GHGs than hybrid electric vehicles (HEVs) or conventional vehicles. For moderate charging intervals of 20–100 miles, PHEVs release fewer GHGs, but HEVs have lower lifetime costs. High fuel prices, low-cost batteries, or high carbon taxes combined with low-carbon electricity generation would make small-capacity PHEVs cost competitive for a wide range of drivers. In contrast, increased battery specific energy or carbon taxes without decarbonization of the electricity grid would have limited impact. Large-capacity PHEVs sized for 40 or more miles of electric-only travel do not offer the lowest lifetime cost in any scenario, although they could minimize GHG emissions for some drivers and provide potential to shift air pollutant emissions away from population centers. The tradeoffs identified in this analysis can provide a space for vehicle manufacturers, policymakers, and the public to identify optimal decisions for PHEV design, policy and use. Given the alignment of economic, environmental, and national security objectives, policies aimed at putting PHEVs on the road will likely be most effective if they focus on adoption of small-capacity PHEVs by urban drivers who can charge frequently.     

Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands

This study assesses the electricity demand pattern in the relatively temperate climate of the Netherlands (latitude 52°30′N). Daily electricity demand and average temperature during the period from 1970 until 2007 are investigated for possible trends in the temperature dependence of electricity demand. We hypothesize that the increased use of cooling applications has shifted the temperature dependence of electricity demand upwards in summer months. Our results show significant increases in temperature dependence of electricity demand in May, June, September, October and during the summer holidays. During the period studied, temperature dependence in these months has shifted from negative to positive, meaning that a higher temperature now leads to an increased electricity demand in these months, rather than a decreased demand as observed historically. Although electricity demand in countries with moderate summer temperatures such as the Netherlands generally peaks in winter months and shows a minimum in summer months, this trend may signal the development of an additional peak in summer, especially given the expected climatic change. As power generating capacity may be negatively influenced by higher temperatures due to decreasing process cooling possibilities, an increasing electricity demand at higher temperatures may have important consequences for power generation capacity planning and maintenance scheduling.     

Cost and emissions impacts of plug-in hybrid vehicles on the Ohio power system

Plug-in hybrid electric vehicles (PHEVs) have been promoted as a potential technology that can reduce vehicles’ fuel consumption, decreasing transportation-related emissions and dependence on imported oil. The net emission and cost impacts of PHEV use are intimately connected with the electricity generator mix used for PHEV charging, which will in turn depend on when during the day PHEVs are recharged. This paper analyzes the effects of a PHEV fleet in the state of Ohio. The analysis considers two different charging scenarios—a controlled and an uncontrolled scenario—which offer the grid operator different levels of control over the timing of PHEV charging. The analysis shows that PHEV use could result in major reductions in gasoline consumption of close to 70% per vehicle compared to a conventional vehicle (CV) under both charging scenarios. Moreover, despite the high penetrations of coal in the Ohio power system, net CO₂ emissions from a PHEV could be up to 24% lower than that of a CV in the uncontrolled case, however, CO₂ and NO_x emissions would increase in both scenarios.