Abstract
The added load that a PHEV (Plug-in Hybrid Electric Vehicle) fleet imposes on the existing electrical grid is of great concern to the electric utility industry. In this paper, analysis was done for a PHEV fleet which consists of 6 PHEVs that were instrumented using data loggers for a period of approximately one year. Systematic analysis using a clustering approach was carried out for the real world velocity profiles. A driving pattern recognition algorithm was developed based on the clustering of the results and Markov-chain model was used for the stochastic velocity generation for different driving patterns. The work of this paper is a part of a larger project in which a mass simulation of a neighborhood of PHEVs will be conducted based on statistical representations of key factors such as vehicle usage patterns, vehicle characteristics, and market penetration of PHEVs.
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