Plug-in Hybrid Electric Vehicles Fleet Research Articles

Impact of plug-in hybrid electric vehicles on thermal generation expansion with high wind penetration

By 2030, the Australian government intends to increase the market share of electric vehicles by at least 50%. This paper investigates the effect of the upcoming large-scale implementation of plug-in hybrid electric vehicles (PHEVs) in Australia on thermal power generation expansion decisions and integration of wind power into New South Wales (NSW), the largest regional market in the Australian National Electricity Market (NEM). Furthermore, seeking to understand whether optimizing and allocating PHEV charging loads can effectively decrease investments and operational costs of the power system with high wind penetration, we also evaluate the potential cost savings from the dedicated governmental charging strategy of PHEV fleets. To this end, we develop a Mixed Integer Linear Programming (MILP) optimization model for optimal power system investment decisions. The simulation results demonstrate that, grid-connected PHEVs obviously increase power system financial and operational burdens. When compared to the scenario with dumb charging strategy, smart charging strategy results in less investment in thermal generation and flatter load curve, as well as less wind curtailment.

Exploiting PHEV to Augment Power System Reliability

Environmental concerns with gasoline vehicles have led to increased attention to electric vehicles in recent years. Plug-in hybrid electric vehicles (PHEV) use both electricity and gasoline to propel the vehicle, and is being recognized as a potential alternative to conventional vehicles. PHEVs offer opportunity to use electric energy generated by renewable resources and significantly reduce greenhouse gas emissions. The electric energy requirement of PHEV can, however, cause negative impacts on the power system reliability, especially when the size of a PHEV fleet is relatively large. This paper presents the development of a probabilistic model considering the driving distance, charging times, charging locations, battery state of charge, and charging requirements of a PHEV. A methodology using hybrid analytical and Monte Carlo simulation approach is presented to evaluate the reliability of a power system integrated with PHEVs, considering the important PHEV characteristics, charging scenarios, and power system parameters. Studies are presented on the IEEE-reliability test system to illustrate the impact of PHEV penetration in a power system. Based on the study results, the methods of augmenting system reliability through controlled PHEV charging are presented in this paper.

The Use of Plug-In Hybrid Electric Vehicles for Peak Shaving

This article is a feasibility analysis of using the batteries in plug-in hybrid electric vehicles (PHEVs) for peak shaving. The analysis focuses on energy availability of the PHEV fleet as well as the financial savings to the utilities by analyzing different charging scenarios and circuitry. The energy availability and the financial savings are heavily dependent on the location and availability of charging stations. Three charging scenarios are analyzed: charging is possible at any time; cars can only be charged overnight; and charging can be done overnight and twice during the day at the place of work for cars used for commuting. The major findings of the study are that charging only overnight will not provide sufficient energy when needed, but both other charging mechanisms can provide effective peak shaving. The charging anytime would require funding a large number of charging station, but charging overnight and at work could be accomplished with relative minor financial investments. The savings from peak shaving could be used for incentives to offset the extra cost of batteries in plug-in electric vehicles (EVs).

Market-Based Optimal Control of Plug-In Hybrid Electric Vehicle Fleets and Economic Analysis

AbstractThis paper proposes an optimization algorithm for coordinating charging/discharging activities of plug-in hybrid electric vehicles (PHEVs) within the electricity market environment. PHEV Fleets are considered as a promising solution to provide vehicle-to-grid (V2G) services. The interactions between PHEVs and the power grid will bring many challenges to the current power market. In this paper, V2G is taken into account in the ancillary service market for providing frequency regulation service. Large-scale PHEV fleet integration will cause load volatility and destabilize the grid if it is implemented without proper control. This paper proposes an optimal strategy to maximize the V2G profits while minimizing the charging costs. The optimal strategy is based on the price forecast for both residential electricity and market regulation. Because of the stochastic nature of electricity price, the proposed optimal problem is solved using stochastic dynamic programming to obtain an optimal solution with th...

Optimal control of plug-in hybrid electric vehicles in frequency regulation service

Growing penetration of plug–in hybrid electric vehicles (PHEVs) places significant impacts on grid, either as electric loads or potential valued vehicle–to–grid (V2G) services. This paper proposes an optimisation strategy to recharge PHEVs batteries with minimum charging cost as well as to produce desired power for grid frequency regulation. The cost arising from the battery charging and the revenue obtained by providing regulation are investigated and represented mathematically. Dynamic programming (DP) algorithm is applied to construct the problem and to compute the optimal controlling strategy for a fleet of PHEVs. Battery state–of–charge (SoC) and charging current are taken as the state factor and control factor of the objective function. Driving energy demand and regulation requirements are treated as disturbances in objective function. Pricing data in cost function and load data in objective function are original from PJM. Simulations are provided to illustrate the optimality of the proposed strategy in 24 hours with variations of parameters.

Power system operation risk analysis considering charging load self-management of plug-in hybrid electric vehicles

Many jurisdictions around the world are supporting the adoption of electric vehicles through incentives and the deployment of a charging infrastructure to reduce greenhouse gas emissions. Plug-in hybrid electric vehicles (PHEVs), with offer mature technology and stable performance, are expected to gain an increasingly larger share of the consumer market. The aggregated effect on power grid due to large-scale penetration of PHEVs needs to be analyzed. Nighttime-charging which typically characterizes PHEVs is helpful in filling the nocturnal load valley, but random charging of large PHEV fleets at night may result in new load peaks and valleys. Active response strategy is a potentially effective solution to mitigate the additional risks brought by the integration of PHEVs. This paper proposes a power system operation risk analysis framework in which charging load self-management is used to control system operation risk. We describe an interactive mechanism between the system and PHEVs in conjunction with a smart charging model is to simulate the time series power consumption of PHEVs. The charging load is managed with adjusting the state transition boundaries and without violating the users’ desired charging constraints. The load curtailment caused by voltage or power flow violation after outages is determined by controlling charging power. At the same time, the system risk is maintained under an acceptable level through charging load self-management. The proposed method is implemented using the Roy Billinton Test System (RBTS) and several PHEV penetration levels are examined. The results show that charging load self-management can effectively balance the extra risk introduced by integration of PHEVs during the charging horizon.

Effectiveness of smart charging of electric vehicles under power limitations

SUMMARY 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.

Time-dependent plug-in hybrid electric vehicle charging based on national driving patterns and demographics

Plug-in hybrid electric vehicles (PHEVs) are one promising technology for addressing concerns around petroleum consumption, energy security and greenhouse gas emissions. However, there is much uncertainty in the impact that PHEVs can have on energy consumption and related emissions, as they are dependent on vehicle technology, driving patterns, and charging behavior. A methodology is used to simulate PHEV charging and gasoline consumption based on driving pattern data in USDOT’s National Household Travel Survey. The method uses information from each trip taken by approximately 170,000 vehicles to track their battery state of charge throughout the day, and to determine the timing and quantity of electricity and gasoline consumption for a fleet of PHEVs. Scenarios were developed to examine the effects of charging location, charging rate, time of charging and battery size. Additionally, demographic information was examined to see how driver and household characteristics influence consumption patterns. Results showed that a compact vehicle with a 10.4kWh useable battery (approximately a 42mile [68km] all electric range) travels between 62.5% and 75.7% on battery electricity, depending on charging scenario. The percent of travel driven electrically (Utility Factor, UF) in a baseline charging scenario increased from 64.3% using 2001 NHTS data to 66.7% using 2009 data. The average UF was 63.5% for males and 72.9% for females and in both cases they are highly sensitive to age. Vehicle charging load profiles across charging scenarios and demographics show a varying effect on summertime peak load, which can be useful for PHEV market segmentation and electric utility planning.

Optimized energy management for large organizations utilizing an on-site PHEV fleet, storage devices and renewable electricity generation

This paper focuses on the daily electricity management problem for organizations with a large number of employees working within a relatively small geographic location. The organization manages its electric grid including limited on-site energy generation facilities, energy storage facilities, and plug-in hybrid electric vehicle (PHEV) charging stations installed in the parking lots. A mixed integer linear program (MILP) is modeled and implemented to assist the organization in determining the temporal allocation of available resources that will minimize energy costs. We consider two cost compensation strategies for PHEV owners: (1) cost equivalent battery replacement reimbursement for utilizing vehicle to grid (V2G) services from PHEVs; (2) gasoline equivalent cost for undercharging of PHEV batteries. Our case study, based on the Oak Ridge National Laboratory (ORNL) campus, produced encouraging results and substantiates the importance of controlled PHEV fleet charging as opposed to uncontrolled charging methods. We further established the importance of realizing V2G capabilities provided by PHEVs in terms of significantly reducing energy costs for the organization.

Virtual PHEV fleet study based on Monte Carlo simulation

The characteristics of electric power generation, transmission and distribution in the USA are such that experts have clearly identified local distribution as the most likely component of the chain to be adversely affected by unregulated Plug-in Hybrid Electric Vehicle (PHEV) charging. This paper presents a study performed to find the impact of PHEV charging on the local distribution transformer. Monte Carlo based mass simulation of highly clustered PHEVs was conducted based on statistical representations of some key factors like vehicle characteristics and vehicle usage patterns. The presented methodology may assist in determining the most suitable local/regional charging strategies for PHEVs.

Plug-in hybrid electric vehicles as a way to maximize the integration of variable renewable energy in power systems: The case of wind generation in northeastern Brazil

Several studies have proposed different tools for analyzing the integration of variable renewable energy into power grids. This study applies an optimization tool to model the expansion of the electric power system in northeastern Brazil, enabling the most efficient dispatch of the variable output of the wind farms that will be built in the region over the next 20 years. The expected combined expansion of wind generation with conventional inflexible generation facilities, such as nuclear plants and run-of-the-river hydropower plants, poses risks of future mismatch between supply and demand in northeastern Brazil. Therefore, this article evaluates the possibility of using a fleet of plug-in hybrid electric vehicles (PHEVs) to regularize possible energy imbalances. Findings indicate that a dedicated fleet of 500 thousand PHEVs in 2015, and a further 1.5 million in 2030, could be recharged overnight to take advantage of the surplus power generated by wind farms. To avoid the initial costs of smart grids, this article suggests, as a first step, the use of a governmental PHEV fleet that allows fleet managers to control battery charging times. Finally, the study demonstrates the advantages of optimizing simultaneously the power and transport sectors to test the strategy suggested here.

Net Air Emissions from Electric Vehicles: The Effect of Carbon Price and Charging Strategies

Plug-in hybrid electric vehicles (PHEVs) may become part of the transportation fleet on time scales of a decade or two. We calculate the electric grid load increase and emissions due to vehicle battery charging in PJM and NYISO with the current generation mix, the current mix with a $50/tonne CO(2) price, and this case but with existing coal generators retrofitted with 80% CO(2) capture. We also examine all new generation being natural gas or wind+gas. PHEV fleet percentages between 0.4 and 50% are examined. Vehicles with small (4 kWh) and large (16 kWh) batteries are modeled with driving patterns from the National Household Transportation Survey. Three charging strategies and three scenarios for future electric generation are considered. When compared to 2020 CAFE standards, net CO(2) emissions in New York are reduced by switching from gasoline to electricity; coal-heavy PJM shows somewhat smaller benefits unless coal units are fitted with CCS or replaced with lower CO(2) generation. NO(X) is reduced in both RTOs, but there is upward pressure on SO(2) emissions or allowance prices under a cap.

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 CO 2 emissions from a PHEV could be up to 24% lower than that of a CV in the uncontrolled case, however, CO 2 and NO x emissions would increase in both scenarios.

The Value of Plug-In Hybrid Electric Vehicles as Grid Resources

Plug-in hybrid electric vehicles (PHEVs) can become valuable resources for an electric power system by providing vehicle to grid (V2G) services, such as energy storage and ancillary services. We use a unit commitment model of the Texas power system to simulate system operations with different-sized PHEV fleets that do and do not provide V2G services, to estimate the value of those services. We demonstrate that a PHEV fleet can provide benefits to the system, mainly through the provision of ancillary services, reducing the need to reserve conventional generator capacity. Moreover, our analysis shows that PHEV owners are made better off by providing V2G services and we demonstrate that these benefits can reduce the time it takes to recover the higher upfront capital cost of a PHEV when compared to other vehicle types.

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.