Queuing Model for EVs Energy Management: Load Balancing Algorithms Based on Decentralized Fog Architecture

Abstract : This paper presents a decentralized scheduling architecture for Electric Vehicles (EVs) energy management based on fog computing paradigm, where optimal load balancing algorithms are implemented using priority-queuing model. The proposed architecture consists of multiple decentralized fog operation centers that assist vehicle-to-grid (V2G) communication in order to manage and schedule EVs charging/discharging requests in real-time way and to maintain the electric smart grid stability. We introduce two scheduling algorithms; 1) priority levels assignment, 2) optimal load balancing of EVs requests over fog servers. The extensive simulations and comparisons with different scenarios proved that our proposed model reduces the response time and maximizes EVs utility. In addition, the proposed scheduling algorithms optimize the energy load during peak hours, and maintain the micro grid stability using real scenarios in the city of Toronto.
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Conference papers
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https://hal-utt.archives-ouvertes.fr/hal-02274651
Contributor : Jean-Baptiste Vu Van <>
Submitted on : Friday, August 30, 2019 - 10:12:52 AM
Last modification on : Monday, September 16, 2019 - 4:35:42 PM

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  • HAL Id : hal-02274651, version 1

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Djabir Abdeldjalil Chekired, Lyes Khoukhi, Hussein Mouftah. Queuing Model for EVs Energy Management: Load Balancing Algorithms Based on Decentralized Fog Architecture. 2018 IEEE International Conference on Communications (ICC 2018), May 2018, Kansas City, United States. pp.1-6. ⟨hal-02274651⟩

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