Abstract

The number of plug-in electric vehicles (PEVs) has rapidly increased owing to the government’s active promotion policy worldwide. Consequently, in the near future, their charging demand is expected to grow enough for consideration in the planning process of the transmission system. This study proposes a stochastic method for modeling the PEV charging demand, of which the time and amount are uncertain. In the proposed method, the distribution of PEVs is estimated by the substations based on the number of electricity customers, PEV expansion target, and statistics of existing vehicles. An individual PEV charging profile is modeled using the statistics of internal combustion engine (ICE) vehicles driving and by aggregating the PEV charging profiles per 154 kV substation, the charging demand of PEVs is determined for consideration as part of the total electricity demand in the planning process of transmission systems. The effectiveness of the proposed method is verified through case studies in the Korean power system. It was found that the PEV charging demand has considerable potential as the additional peak demand in the transmission system planning because the charging time could be concentrated in the evening peak time.

Highlights

  • As part of the efforts to reduce greenhouse gas emission in the transportation field, the number of electric vehicles (EV) has rapidly increased with the active promotion policy of governments all over the world [1,2]

  • Considering the charging efficiency(6): of the of the plug-in electric vehicles (PEVs) charger, the total charging demand of the to the power system is calculated by PEV charger, the total charging demand of the PEV to the power system is calculated by Equation (6):

  • Based on the total charging profile of the PEVs over the substations, their total charging demand can be determined as the value at the time when the feasibility of the transmission system is analyzed with assumed conditions for the load and renewable energy resources in the planning process as represented by the Equation (9): Ps = Ps (t∗ )

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Summary

Introduction

As part of the efforts to reduce greenhouse gas emission in the transportation field, the number of electric vehicles (EV) has rapidly increased with the active promotion policy of governments all over the world [1,2]. The charging demands of PEVs need to be modelled as a part of the electricity loads at the substation so that it can be considered in the process of transmission system planning where the process is more heavily regulated and conducted in a longer timeframe comparing with the distribution system. The uniform distribution model could not consider variations in the penetration level and distribution of EVs, which are necessary for the consideration of the EV charging demand in the planning process of transmission systems. In theusing distribution and charging profiles of the PEVs. PEVs is estimated the154 substation based on the the number of demand electricity of PEVs customers, the for PEVconsideration expansion target,as and Anelectricity individual PEV charging can be determined a existing part ofstatistics. The effectiveness of the proposed is verified case studiesininthe theevening Korean power system and it was found that the PEV charging demand has considerable potential as a peak demand in the transmission system planning Demand because theof charging time is concentrated in the evening peak time

Penetration
Distribution of PEVs
Stochastic method thenumber number
Stochastic modeling for distribution ofbefore
Stochastic
SoC from
Charging
Charging Demand of PEVs per Substation
Case StudyFigure
Distribution of PEVs in Korean Power System
Modeling
Characteristics Analysis of PEV Charging Demand
14. Comparing
Discussion
Conclusions
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