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Modeling of Plug-in Hybrid Electric Vehicle Charging Demand in Probabilistic Power Flow Calculations

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2 Author(s)
Gan Li ; School of Electronic, Electrical and Computer Engineering, University of Birmingham, Edgbaston, UK ; Xiao-Ping Zhang

Millions of electric vehicles (EVs), especially plug-in hybrid EVs (PHEVs), will be integrated into the power grid in the near future. Due to their large quantity and complex charging behavior, the impact of substantial PHEVs charging on the power grid needs to be investigated. Since the charging behavior of PHEVs in a certain regional transmission network or a local distribution network is determined by different uncertain factors, their overall charging demand tends to be uncertain and in this situation probabilistic power flow (PPF) can be applied to analyze the impact of PHEVs charging on the power grid. However, currently there is no suitable model of the overall charging demand of PHEVs available for PPF calculations. In this paper, a methodology of modeling the overall charging demand of PHEVs is proposed. The proposed methodology establishes a single PHEV charging demand model, and then employs queuing theory to describe the behavior of multiple PHEVs. Moreover, two applications are given, i.e., modeling the overall charging demand of PHEVs at an EV charging station and in a local residential community, respectively. Comparison between PPF calculations and Monte Carlo simulation are made on a modified IEEE 30-bus system integrated with the two demand models proposed.

Published in:

IEEE Transactions on Smart Grid  (Volume:3 ,  Issue: 1 )