Risk Analysis of Electric Vehicles Connected to the Cyber-physical Power System

Li, Manli; Ni, Ming; Tong, Heqin; Ru, Yingtao; Xu, Jinjiang; Wu, Yingjun

doi:10.1109/ispec53008.2021.9735933

Cited by 1 publication

(1 citation statement)

References 26 publications

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“…With the increasing number of EVs and the improvement of load aggregation technology and market, a wider range of EV flexibility resources can be used to reduce the carbon emissions of the IDCs and improve their sustainability. In addition, Li M. analyzed the cyber security risks that may have existed when EVs were connected to the cyber-physical power system [26].…”

Section: Previous Workmentioning

confidence: 99%

A Sustainability Improvement Strategy of Interconnected Data Centers Based on Dispatching Potential of Electric Vehicle Charging Stations

Wang

Liu

et al. 2022

Sustainability

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With the rapid development of information technology, the electricity consumption of Internet Data Centers (IDCs) increases drastically, resulting in considerable carbon emissions that need to be reduced urgently. In addition to the introduction of Renewable Energy Sources (RES), the joint use of the spatial migration capacity of IDC workload and the temporal flexibility of the demand of Electric Vehicle Charging Stations (EVCSs) provides an important means to change the carbon footprint of the IDC. In this paper, a sustainability improvement strategy for the IDC carbon emission reduction was developed by coordinating the spatial-temporal dispatch flexibilities of the IDC workload and the EVCS demand. Based on the Minkowski sum algorithm, a generalized flexible load model of the EVCSs, considering traffic flow and Road Impedance (RI) was formulated. The case studies show that the proposed method can effectively increase the renewable energy consumption, reduce the overall carbon emissions of multi-IDCs, reduce the energy cost of the DCO, and utilize the EV dispatching potential. Discussions are also provided on the relationship between workload processing time delay and the renewable energy consumption rate.

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Section: Previous Workmentioning

confidence: 99%