Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation

Guo, Zhaomiao; Zhou, Zhi; Zhou, Yan

doi:10.1109/tste.2019.2916499

Title: Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation

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Abstract

Autonomous electric vehicles (AEVs) provide unique opportunities to cope with the uncertainties of distributed energy generation in distribution networks. But the effects are limited by both inherent radial topology and the behaviors of decentralized AEVs. As such, we investigate the potential benefits of dynamic distribution network reconfiguration (DDNR), taking into account AEVs' spatial-temporal availability and their charging demand. We propose a mixed integer programming model to optimally coordinate the charging/discharging of AEVs with DDNR, while satisfying AEVs' original travel plan. Numerical studies based on a test system overlaying the IEEE 33-node test feeder and Sioux Falls transportation network show that DDNR and AEV complement each other, which improves the operation of the distribution system. We also conduct sensitivity analyses on inputs including renewable fluctuation and AEVs penetration level.

Authors:

^[1];

^[2]; Zhou, Yan ^[2]

Univ. of Central Florida, Orlando, FL (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)

Publication Date:: Wed Apr 01 00:00:00 EDT 2020

Research Org.:: Argonne National Lab. (ANL), Argonne, IL (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

OSTI Identifier:: 1657513

Grant/Contract Number:: AC02-06CH11357

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Sustainable Energy

Additional Journal Information:: Journal Volume: 11; Journal Issue: 2; Journal ID: ISSN 1949-3029

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 33 ADVANCED PROPULSION SYSTEMS; Autonomous electric vehicle (AEV); Controllable charging; Urban transportation network; Vehicle-to-grid (V2G); distribution network reconfiguration (DNR)

Citation Formats


                    Guo, Zhaomiao, Zhou, Zhi, and Zhou, Yan. Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation.  United States: N. p., 2020. 
Web.  doi:10.1109/tste.2019.2916499.

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                    Guo, Zhaomiao, Zhou, Zhi, & Zhou, Yan. Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation.  United States.  https://doi.org/10.1109/tste.2019.2916499

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                    Guo, Zhaomiao, Zhou, Zhi, and Zhou, Yan. Wed .  
"Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation".  United States.  https://doi.org/10.1109/tste.2019.2916499.  https://www.osti.gov/servlets/purl/1657513.

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@article{osti_1657513,

  title        = {Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation},

  author       = {Guo, Zhaomiao and Zhou, Zhi and Zhou, Yan},

  abstractNote = {Autonomous electric vehicles (AEVs) provide unique opportunities to cope with the uncertainties of distributed energy generation in distribution networks. But the effects are limited by both inherent radial topology and the behaviors of decentralized AEVs. As such, we investigate the potential benefits of dynamic distribution network reconfiguration (DDNR), taking into account AEVs' spatial-temporal availability and their charging demand. We propose a mixed integer programming model to optimally coordinate the charging/discharging of AEVs with DDNR, while satisfying AEVs' original travel plan. Numerical studies based on a test system overlaying the IEEE 33-node test feeder and Sioux Falls transportation network show that DDNR and AEV complement each other, which improves the operation of the distribution system. We also conduct sensitivity analyses on inputs including renewable fluctuation and AEVs penetration level.},

  doi          = {10.1109/tste.2019.2916499},

  journal      = {IEEE Transactions on Sustainable Energy},

  number       = 2,

  volume       = 11,

  place        = {United States},

  year         = {Wed Apr 01 00:00:00 EDT 2020},

  month        = {Wed Apr 01 00:00:00 EDT 2020}

}

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