EDA-Based Charging Algorithm for Plug-In Hybrid Electric Vehicle to Shift the Peak of Power Supply

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Abstract:

This paper proposes a charging algorithm which is based on the Estimation of Distribution Algorithm (EDA) for Plug in Hybrid Electric Vehicle (PHEV). The proposed algorithm shifts the peak of power supply, satisfies the requested State of Charge (SoC [%]), and minimizes the charging cost. The proposed algorithm uses flexible weight for charging and upper charging limit to each PHEV to minimize the charge amount in peak time. The simulation result shows that the proposed algorithm shifts the peak of power supply in commute time zones, satisfies SoC of 93% PHEVs, and reduces charging cost by 31% compared with conventional EDA algorithm.

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46-50

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December 2012

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] M. Duvall and E. Knipping, Environmental assessment of plug-in hybrid electric vehicles, EPRI Jul. 2007 [Online]. Available: http: /mydocs. epri. com/docs/ CorporateDocuments/SectorPages/Portfolio/PDM/PHEV-ExecSum-vol1. pdf.

Google Scholar

[2] O. Sundstrom, C. Binding Flexible Charging Optimization for Electric Vehicles Considering Distribution Grid Constraints, , IEEE Transaction on Smart Grid, vol 3, no. 1, p.26 – 37, Mar (2012).

DOI: 10.1109/tsg.2011.2168431

Google Scholar

[3] S. Shao, T. Zhang, M. Pipattanasomporn, S. Rahman, Impact of TOU Rates on Distribution Load Shapes in a Smart Grid with PHEV Penetration, in Proc. 2010 IEEE PES Transmission and Distribution Conference and Exposition, New Orleans, LA, U.S.A. April 19-22, (2010).

DOI: 10.1109/tdc.2010.5484336

Google Scholar

[4] W. Su, M. Chow Performance Evaluation of an EDA-Based Large-Scale Plug-In Hybrid Electric Vehicle Charging Algorithm.

DOI: 10.1109/tsg.2011.2151888

Google Scholar

[5] A. Mohsenian-Rad, W.S. Wong, J. Jatskevich, R. Schober, A. Leon-Garcia, Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid, IEEE Transaction on Smart Grid, vol 1, no. 3, Dec (2010).

DOI: 10.1109/tsg.2010.2089069

Google Scholar

[6] C. Guille and G. Gross, The integration of PHEV aggregation into a power system with wind resources, in Proc. Bulk Power Syst. Dyn. Control Symp., Aug. 1–6, 2010, p.1–9.

DOI: 10.1109/irep.2010.5563263

Google Scholar