Electric Vehicle Charging Scheduling Considering Different Charging Demands

Kaile Zhou () and Lulu Wen ()
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Kaile Zhou: Hefei University of Technology
Lulu Wen: Hefei University of Technology

Chapter Chapter 10 in Smart Energy Management, 2022, pp 223-249 from Springer

Abstract: Abstract The uncoordinated charging of large amounts of electric vehicles (EVs) can lead to a substantial surge of peak loads, which could be harmful to the operation of the power system. In this chapter, a coordinated charging scheduling method is provided to achieve peak shaving and valley filling of the microgrid load when EVs are connected. In the method, the charging mode of EVs is selected based on a charging urgency indicator, which is used to measure the charging demand. Then a coordinated charging scheduling optimization model that aims to minimize the overall peak-valley difference of the microgrid load is presented. The optimization model is subject to a series of constraints set for slow charging EVs, fast-charging EVs and microgrid operation. Furthermore, Monte Carlo simulation (MCS) is used to measure the randomness of EVs. The results have shed light on both the selection of charging modes by EV owners and peak shaving and valley filling for microgrid operation. As a result, this model can support a more friendly power supply–demand interaction to accommodate the increasing access of EVs and the rapid development of the flexible microgrid.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-16-9360-1_10

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DOI: 10.1007/978-981-16-9360-1_10

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