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.     

Smart management of distinct plug‐in hybrid electric vehicle charging stations considering mobility pattern and site characteristics

Management of plug‐in hybrid electric vehicles (PHEVs) is an important alternative energy solution to accord the prevailing environmental depletion. However, adding PHEVs to the existing distribution network may stimulate issues such as increase in peak load, power loss, and voltage deviation. Addressing the aforementioned issues by incorporating distinct mobility patterns together will develop an attractive energy management. In this paper, suitable location of the charging station is presented for a novel 2‐area distribution system following distinct mobility patterns. A comprehensive study by considering the optimal, midst, and unfit site for placing the charging station is incorporated. For managing the charging sequence of PHEVs, a meta‐heuristic solving tool is developed. The main contribution of this programming model is its ability to schedule the vehicles simultaneously in both the areas. The efficiency of the proposed energy management framework is evaluated on the IEEE 33‐bus and IEEE 69‐bus distribution systems. The test system is subjected to different scenarios for demonstrating the superior performance of the proposed solving tool in satisfying the convenience of vehicle owner along with reducing the peak demand. The results show that charging at low electricity price period and discharging at high electricity price period enables the minimum operational cost.     

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 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.     

The effects of electricity pricing on PHEV competitiveness

Plug-in hybrid electric vehicles (PHEVs) will soon start to be introduced into the transportation sector, thereby raising a host of issues related to their use, adoption and effects on the electricity sector. Their introduction has the potential to significantly reduce carbon emissions from the transportation sector, which has led to government policies aimed at easing their introduction. If their widespread adoption is set as a target it is imperative to consider the effects of existing policies that may increase or decrease their adoption rate. In this study, we present a micro level electricity demand model that can gauge the effects of PHEVs on household electricity consumption and the subsequent economic attractiveness of the vehicles. We show that the electricity pricing policy available to the consumer is a very significant factor in the economic competitiveness of PHEVs. Further analysis shows that the increasing tier electricity pricing system used in California will substantially blunt adoption of PHEVs in the state; and time of use electricity pricing will render PHEVs more economically attractive in any state.     

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.     

PV powered smart charging station for PHEVs

A huge inrush of PHEVs is envisioned in the future. There is a growing risk that, this proliferation in the number of PHEVs will trigger extreme surges in demand while charging them during rush hours. To mitigate this impact, a smart charging station is proposed in which the charging of the PHEVs is controlled in such a way that the impact of charging during peak load period is not felt on the grid. The power needed to charge the plug in hybrids comes from grid-connected photovoltaic generation or the utility or both. The three way interaction between the PV, PHEVs and the grid ensures optimal usage of available power, charging time and grid stability. The system designed to achieve the desired objective consists of a photovoltaic system, DC/DC boost converter, DC/AC bi-directional converter and DC/DC buck converter. The output of DC/DC boost converter and input of DC/AC bi-directional converter share a common DC link. A unique control strategy based on DC link voltage sensing is proposed for the above system for efficient transfer of energy.     

Potential impacts assessment of plug-in electric vehicles on the Portuguese energy market

Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs), which obtain their fuel from the grid by charging a battery, are set to be introduced into the mass market and expected to contribute to oil consumption reduction. In this research, scenarios for 2020 EVs penetration and charging profiles are studied integrated with different hypotheses for electricity production mix. The impacts in load profiles, spot electricity prices and emissions are obtained for the Portuguese case study. Simulations for year 2020, in a scenario of low hydro production and high prices, resulted in energy costs for EVs recharge of 20 cents/kWh, with 2 million EVs charging mainly at evening peak hours. On the other hand, in an off-peak recharge, a high hydro production and low wholesale prices' scenario, recharge costs could be reduced to 5.6 cents/kWh. In these extreme cases, EV's energy prices were between 0.9€ to 3.2€ per 100 km. Reductions in primary energy consumption, fossil fuels use and CO₂ emissions of up to 3%, 14% and 10%, respectively, were verified (for a 2 million EVs' penetration and a dry year's off-peak recharge scenario) from the transportation and electricity sectors together when compared with a BAU scenario without EVs.     

Comparative impacts of wind and photovoltaic generation on energy storage for small islanded electricity systems

This paper addresses the annual energy storage requirements of small islanded electricity systems with wind and photovoltaic (PV) generation, using hourly demand and resource data for a range of locations in New Zealand. Normalised storage capacities with respect to annual demand for six locations with winter-peaking demand profiles were lower for wind generation than for PV generation, with an average PV:wind storage ratio of 1.768:1. For two summer-peaking demand profiles, normalised storage capacities were lower for PV generation, with storage ratios of 0.613:1 and 0.455:1. When the sensitivity of storage was modelled for winter-peaking demand profiles, average storage ratios were reduced. Hybrid wind/PV systems had lower storage capacity requirements than for wind generation alone for two locations. Peak power for storage charging was generally greater with PV generation than with wind generation, and peak charging power increased for the hybrid systems. The results are compared with those for country-scale electricity systems, and measures for minimising storage capacity are discussed. It is proposed that modelling of storage capacity requirements should be included in the design process at the earliest possible stage, and that new policy settings may be required to facilitate a transition to energy storage in fully renewable electricity systems.     

Moving from assumption to observation: Implications for energy and emissions impacts of plug-in hybrid electric vehicles

Plug-in hybrid electric vehicles (PHEVs) are currently for sale in most parts of the United States, Canada, Europe and Japan. These vehicles are promoted as providing distinct consumer and public benefits at the expense of grid electricity. However, the specific benefits or impacts of PHEVs ultimately relies on consumers purchase and vehicle use patterns. While considerable effort has been dedicated to understanding PHEV impacts on a per mile basis few studies have assessed the impacts of PHEV given actual consumer use patterns or operating conditions. Instead, simplifying assumptions have been made about the types of cars individual consumers will choose to purchase and how they will drive and charge them. Here, we highlight some of these consumer purchase and use assumptions, studies which have employed these assumptions and compare these assumptions to actual consumer data recorded in a PHEV demonstration project. Using simulation and hypothetical scenarios we discuss the implication for PHEV impact analyses and policy if assumptions about key PHEV consumer use variables such as vehicle choice, home charging frequency, distribution of driving distances, and access to workplace charging were to change.     

Air quality and environmental impacts of alternative vehicle technologies in Ontario,Canada

This study is focused on the province-wide emissions in Ontario, Canada and urban air pollution in the city of Toronto. The life-cycle (LC) impacts of utilizing alternative fuels for transportation purposes is considered in terms of six major stressors for climate change, acidification and urban air quality. The vehicles considered are plug-in hybrid electric vehicles (PHEVs), fuel cell vehicles (FCVs) and fuel cell plug-in hybrid electric vehicles (FCPHEVs). Modeling of the penetration rates for these types of vehicles has been completed based on the maximum base-load capacity of Ontario's electricity grid to accommodate the generation of hydrogen and charging of vehicles using grid electricity. Results show that the reduction in greenhouse gas emissions from adoption of PHEVs or FCVs will exceed 3% of the current emissions from the transportation sector in Ontario while FCPHEVs may achieve almost twice this reduction. All vehicles exhibit similar impacts on the precursors for photochemical smog although the province-wide effects differ significantly.     

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.     

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.     

Simultaneous planning of plug-in hybrid electric vehicle charging stations and wind power generation in distribution networks considering uncertainties

Recently, plug-in hybrid electric vehicles (PHEV) are becoming more attractive than internal combustion engine vehicles (ICEV). Hence, design and modeling of charging stations (CSs) has vital importance in distribution system level. In this paper, a new formulation for PHEV charging stations is presented with the strategic presence of wind power generation (WPG). This study considers constraints of the system losses, the regulatory voltage limits, and the charge/discharge schedule of PHEV based on the social behavior of drivers for appropriate placement of PHEV charging stations in electricity grid. The role of CSs and WPG units must be correctly assessed to optimize the investment and operation cost for the whole system. However, the wind generation owners (WGOs) have different objective functions which might be contrary to the objectives of distribution system manager (DSM). It is assumed that aggregating and management of charge/discharge program of PHEVs are smartly carried out by DSM. This paper presents a long-term bi-objective model for optimal planning of PHEV charging stations and WPG units in distribution systems which simultaneously optimize two objectives, namely the benefits of DSM and WGO. It also considers the uncertainty of load growth, electricity price and PHEV access to the charging station using Mont-Carlo simulation (MCS) method. Initial state of charge uncertainty is also modeled based on scenario approach in PHEV batteries and wind turbine power generation using weibull distribution. Non dominated sorting genetic algorithm (NSGA-II) is used to solve the optimization problem. The simulation has been conducted on the nine-bus system.     

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.     

Implications of a US electricity standard for final energy demand

This paper analyzes the emissions impact of an emissions intensity standard (metric tons of CO₂ per MWh of electricity) for the US power sector on US final energy demand — i.e. the manufacturing, residential, commercial, and transportation sectors. An emissions intensity standard, although geared towards the power sector, will have implications for these other sectors of the economy through its effect on economy-wide energy prices. Using a hybrid energy-economy simulation model (CIMS), we find the effect on aggregate emissions from final demand to mostly be small. However, after disaggregating final demand, we find significant changes in CO₂e emissions for several of sub-sectors. Given that emissions reductions in final energy demand are needed alongside power sector reductions for the US to achieve deep emissions cuts, our findings provide needed insight as to whether these eventual reductions will be helped or hindered by a US electricity standard.     

Transmission network-based energy and environmental assessment of plug-in hybrid electric vehicles

The introduction of plug-in hybrid electric vehicles (PHEVs) is expected to have a significant impact on regional power systems and pollutant emissions. This paper analyzes the effects of various penetrations of PHEVs on the marginal fuel dispatch of coal, natural gas and oil, and on pollutant emissions of CO₂, NO_x, SO₂ in the New York Metropolitan Area for two battery charging scenarios in a typical summer and winter day. A model of the AC transmission network of the Northeast Power Coordinating Council (NPCC) region with 693 generators is used to realistically incorporate network constraints into an economic dispatch model. A data-based transportation model of approximately 1 million commuters in NYMA is used to determine battery charging pattern. Results show that for all penetrations of PHEVs network-constrained economic dispatch of generation is significantly more realistic than unconstrained cases. Coal, natural gas and oil units are on the margin in the winter, and only natural gas and oil units are on the margin in the summer. Hourly changes in emissions from transportation and power production are dominated by vehicular activity with significant overall emissions reductions for CO₂ and NO_x, and a slight increase for SO₂. Nighttime regulated charging produces less overall emissions than unregulated charging from when vehicles arrive home for the summer and vice versa for the winter. As PHEVs are poised to link the power and transportation sectors, data-based models combining network constraints and economic dispatch have been shown to improve understanding and facilitate control of this link.     

Effectiveness of smart charging of electric vehicles under power limitations

This article investigates charging strategies for plug‐in hybrid electric vehicles (PHEV) as part of the energy system. The objective was to increase the combined all‐electric mileage (total distance driven using only the traction batteries in each PHEV) when the total charging power at each workplace is subject to severe limitations imposed by the energy system. In order to allocate this power optimally, different input variables, such as state‐of‐charge, battery size, travel distance, and parking time, were considered. The required vehicle mobility was generated using a novel agent‐based model that describes the spatiotemporal movement of individual PHEVs. The results show that, in the case of Helsinki (Finland), smart control strategies could lead to an increase of over 5% in the all‐electric mileage compared to a no‐control strategy. With a high prediction error, or with a particularly small or large battery, the benefits of smart charging fade off. Smart PHEV charging strategies, when applied to the optimal allocation of limited charging power between the cars of a vehicle fleet, seem counterintuitively to provide only a modest increase in the all‐electric mileage. A simple charging strategy based on allocating power to PHEVs equally could thus perform sufficiently well. This finding may be important for the future planning of smart grids as limiting the charging power of larger PHEV fleets will sometimes be necessary as a result of grid restrictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Storage and Demand Side Management as power generator’s strategic instruments to influence demand and prices

Classic storage utilisation is mainly based on charging/discharging strategies enabling a power generation company to generate revenues by buying electricity in low-price periods and selling it at higher prices. Within this paper another feasible way to gain arbitrage in storage utilisation is considered: Strategically increasing demand disregarding existing market prices. This means, charging electricity for storage is not only bought in low price periods, but in all periods where storage charging could influence demand so that market prices increase. This idea is expanded by focussing on another frequently discussed topic which could serve utilities for the same purpose: Automated Demand Side Management (DSM). By using data from Ontario’s electricity market and applying a particular storage and DSM strategy it is analysed to which extent a non-regulated dominant power generation company could influence hourly demand and corresponding prices. It turns out that both strategies analysed derive additional revenues for the dominant power generation company compared to a Business-as-Usual (BAU) case. The results provide an indicator of potential threats for misuse from particular storage or DSM utilisation. Therefore, especially in countries where DSM and/or storage applications are still in its fledgling stages, appropriate market surveillance has to be guaranteed.