Impact of charging efficiency variations on the effectiveness of variable-rate-based charging strategies for electric vehicles

Amoroso, F. A.; Cappuccino, G.

doi:10.1016/j.jpowsour.2011.07.074

Cited by 30 publications

(11 citation statements)

References 9 publications

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“…Strategists may also allocate variable charging rates for each PEV to balance the aggregate load. Amoroso and Cappuccino [59] proposed two methods to calculate charging rates. One is the maximum energy with priority, which sets the charging power as the maximum from all energy requests, and the other is called spread energy with priority, which calculates the rate by dividing the total required energy with the entire available time period.…”

Section: Aggregator Strategymentioning

confidence: 99%

Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review

Yang

Foley

2015

Renewable and Sustainable Energy Reviews

198

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Section: Aggregator Strategymentioning

confidence: 99%

Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review

Yang

Foley

2015

Renewable and Sustainable Energy Reviews

198

View full text Add to dashboard Cite

“…Strategist may also allocate variable charging rate for each of the PEVs to balance the aggregate load. Amoroso and Cappuccino (2011) proposed two methods to calculate charging rates. One is the maximum energy with priority, which sets the charging power as the maximum from all energy requests, and the other is called spread energy with priority, which calculates the rate by dividing the total required energy with the entire available time period.…”

Section: Analytical Charging Strategies For Integrating Pevs With Powmentioning

confidence: 99%

Optimal Scheduling Methods to Integrate Plug-in Electric Vehicles with the Power System: A Review

Yang

Foley

et al. 2014

IFAC Proceedings Volumes

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“…If the vehicle commuting share (VCS), i.e., the percentage of all work related journeys that are conducted by a vehicle, is known for the city or country, the number of vehicles commuting to work in an area can be calculated according to (23), and the vehicles commuting back home to the area according to (24): Due to differences in vehicle density (i.e., number of vehicles/ persons) between the districts, it is assumed that VCS varies for the districts and also for the DS, i.e., the number of persons commuting with a vehicle will probably be higher for a district with a high vehicle density than for a district with a lower vehicle density. The VCS for the DS is calculated according to (25):…”

Section: B Estimation Of Number Of Vehicles and Their Usagementioning

confidence: 99%

“…Transferring power from the grid to the batteries involves losses both in the charge equipment and in the battery itself. As discussed in [21] and [23], the charge efficiency varies for different operating points of the charger. However, since the operating point is assumed to be constant (constant charge power), the efficiency is also assumed to be constant.…”

Section: B Estimation Of Number Of Vehicles and Their Usagementioning

confidence: 99%

Assessment of Electric Vehicle Charging Scenarios Based on Demographical Data

Steen

Tuấn

Carlson

et al. 2012

IEEE Trans. Smart Grid

126

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A massive introduction of plug-in electric vehicles (PEVs) in the transportation sector would likely increase the total electricity consumption. Depending on how and when the PEVs are charged, the effects on the power demand will vary. Previous studies have shown that uncontrolled charge of PEVs can cause problems for the distribution system in some areas. This paper proposes an approach to control PEVs charging based on the charging behavior estimated from the demographical statistical data. In this approach, three different charge strategies are designed and the impacts of PEVs charging on the distribution system is assess using standard load flow calculations. A case study using the proposed approach examines the real situation in Gothenburg, a city on the west coast of Sweden. The results from the study show that the impacts on the distribution system due to PEVs vary between different areas. By controlling the charging, the impacts can be reduced but the choice of control methods must be chosen carefully. Furthermore, the results indicate that a well-developed public charging infrastructure could reduce the stress on the residential distribution systems since part of the charging can be done in commercial areas. Index Terms-Electric distribution system, electric vehicle (EV), open loop radial distribution system, plug-in electric vehicle (PEV), plug-in hybrid electric vehicle (PHEV). LIST OF NOMENCLATURES AND SYMBOLS EPSElectric power system. DSO Distribution system operator. DS Electrical distribution system. OLR-DS Open loop radial distribution system. EV Electric vehicle. PHEV Plug-in hybrid electric vehicle. PEV Plug-in electric vehicle. DG Distributed generation. DES Distributed energy storage. V2G Vehicle To grid. Maximum number of PEVs.

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Impact of charging efficiency variations on the effectiveness of variable-rate-based charging strategies for electric vehicles

Cited by 30 publications

References 9 publications

Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review

Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review

Optimal Scheduling Methods to Integrate Plug-in Electric Vehicles with the Power System: A Review

Assessment of Electric Vehicle Charging Scenarios Based on Demographical Data

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