Plug-in hybrid electric vehicle impacts on hourly electricity demand in the United States

Weiller, Claire

doi:10.1016/j.enpol.2011.04.005

Cited by 244 publications

(118 citation statements)

References 16 publications

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“…Several papers deal with PHEV-related subjects, including, but not limited to, range requirement analysis (Pearre et al, 2011;Franke and Krems, 2013), PHEV impacts on the electricity network (Sioshansi and Miller, 2011;Nurre et al, 2014;Arslan and Karaşan, 2013;Galus et al, 2010;Weiller, 2011;Axsen et al, 2011), battery capacity analysis (Albertus et al, 2008;Catenacci et al, 2013;Scrosati and Garche, 2010), environmental impacts (Stephan and Sullivan, 2008;Smith, 2010;Marshall et al, 2013), market analysis (Gardner et al, 2013;Khan and Kockelman, 2012;Axsen and Kurani, 2013;Eppstein et al, 2011) and location optimization of recharging infrastructure (He et al, 2013;Wang and Lin, 2009;MirHassani and Ebrazi, 2012). A summary of recent studies in the literature related to the economics of PHEVs is presented in Table 1.…”

Section: Literature Reviewmentioning

confidence: 99%

Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips

Arslan¹,

Yıldız²,

Karaşan³

2014

Energy Policy

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We investigate the travel costs of CVs, HEVs and PHEVs for long-distance trips. We analyze the impacts of battery, driver and road network characteristics on the costs. We provide critical managerial insights to shape the investment decisions about PHEVs. Drivers' stopping intolerance may hamper the cost and emission benefits of PHEVs. Negative effect of intolerance on cost may be overcome by battery capacity expansion. a r t i c l e i n f o b s t r a c tIn a road network with refueling and fast charging stations, the minimum-cost driving path of a plug-in hybrid electric vehicle (PHEV) depends on factors such as location and availability of refueling/fast charging stations, capacity and cost of PHEV batteries, and driver tolerance towards extra mileage or additional stopping. In this paper, our focus is long-distance trips of PHEVs. We analyze the impacts of battery characteristics, often-overlooked driver preferences and road network features on PHEV travel costs for long-distance trips and compare the results with hybrid electric and conventional vehicles. We investigate the significance of these factors and derive critical managerial insights for shaping the future investment decisions about PHEVs and their infrastructure. In particular, our findings suggest that with a certain level of deployment of fast charging stations, well established cost and emission benefits of PHEVs for the short range trips can be extended to long distance. Drivers' stopping intolerance may hamper these benefits; however, increasing battery capacity may help overcome the adverse effects of this intolerance.

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Section: Literature Reviewmentioning

confidence: 99%

Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips

Arslan¹,

Yıldız²,

Karaşan³

2014

Energy Policy

View full text Add to dashboard Cite

show abstract

“…Additionally, the impact of this total daily charging demand can also be changed depending on how the charging demand would be distributed over 24 h. We assumed two different cases for the charging demand profile in Figure 4 by benchmarking the empirically obtained profiles of Weiller [16].…”

Section: Simulation For An Impact Assessment Of Electric Vehicle Diffmentioning

confidence: 99%

“…The total daily charging demand for electric vehicles changes depends on the penetration ratio of electric vehicles multiplied by the total number of passenger vehicles in Korea. Additionally, the impact of this total daily charging demand can also be changed depending on how the charging demand would be distributed over 24 h. We assumed two different cases for the charging demand profile in Figure 4 by benchmarking the empirically obtained profiles of Weiller [16]. .…”

Section: Simulation For An Impact Assessment Of Electric Vehicle Diffmentioning

confidence: 99%

“…Weiller [16] studied how different charging behaviors of plug-in hybrid electric vehicles (PHEVs) affect the electricity demand profile in the US. He developed a simulation algorithm for estimating the charging profiles with plug-in times and initial state-of-charge of batteries, finding that PHEV charging may increase the power system load by 560-910 W per vehicle, based on the developed estimation algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

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Key Features of Electric Vehicle Diffusion and Its Impact on the Korean Power Market

et al. 2018

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Abstract:The market share of electric vehicles is growing and the interest in these vehicles is rapidly increasing in industrialized countries. In the light of these circumstances, this study provides an integrated policy-making package, which includes key features for electric vehicle diffusion and its impact on the Korean power market. This research is based on a quantitative analysis with the following steps: (1) it analyzes drivers' preferences for electric or traditional internal combustion engine (ICE) vehicles with respect to key automobile attributes and these key attributes indicate what policy makers should focus on; (2) it forecasts the achievable level of market share of electric vehicles in relation to improvements in their key attributes; and (3) it evaluates the impact of electric vehicle diffusion on the Korean power market based on an achievable level of market share with different charging demand profiles. Our results reveal the market share of electric vehicles can increase to around 40% of the total market share if the key features of electric vehicles reach a similar level to those of traditional vehicles. In this estimation, an increase in the power market's system generation costs will reach around 10% of the cost in the baseline scenario, which differs slightly depending on charging demand profiles.

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“…The adverse effects of high penetration level of EVs on the power grid when they charge themselves in the grid to vehicle (G2V) mode are briefly reviewed in [3]. However, in the vehicle to grid (V2G) mode, active and reactive power injected to the network by EVs, if controlled well, can decrease the peak power [12] and provide ancillary services [13] instead of causing adverse effects. Therefore, although most of existing DSM programs neglect the technical constraints of the power system to simplify mathematical calculations [11], considering the technical constraints is critical for practical deployment of future power systems.…”

Section: Introductionmentioning

confidence: 99%

Transactive Demand Side Management Programs in Smart Grids with High Penetration of EVs

et al. 2017

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Due to environmental concerns, economic issues, and emerging new loads, such as electrical vehicles (EVs), the importance of demand side management (DSM) programs has increased in recent years. DSM programs using a dynamic real-time pricing (RTP) method can help to adaptively control the electricity consumption. However, the existing RTP methods, particularly when they consider the EVs and the power system constraints, have many limitations, such as computational complexity and the need for centralized control. Therefore, a new transactive DSM program is proposed in this paper using an imperfect competition model with high EV penetration levels. In particular, a heuristic two-stage iterative method, considering the influence of decisions made independently by customers to minimize their own costs, is developed to find the market equilibrium quickly in a distributed manner. Simulations in the IEEE 37-bus system with 1141 customers and 670 EVs are performed to demonstrate the effectiveness of the proposed method. The results show that the proposed method can better manage the EVs and elastic appliances than the existing methods in terms of power constraints and cost. Also, the proposed method can solve the optimization problem quick enough to run in real-time.

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Plug-in hybrid electric vehicle impacts on hourly electricity demand in the United States

Cited by 244 publications

References 16 publications

Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips

Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips

Key Features of Electric Vehicle Diffusion and Its Impact on the Korean Power Market

Transactive Demand Side Management Programs in Smart Grids with High Penetration of EVs

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