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A Multi-layered Distributed Cloud Network for Cyber-Physical Energy System

  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The diversity of power sources for electricity generation excites the current smart grid to evolve towards Cyber-Physical Energy System (CPES), which integrates with other systems, such as natural gas and heat. By advanced communication technologies, CPES can achieve effective energy fusion, real-time computation and precise control. With the increasing number of energy applications that bring large quantities of data, it calls for sufficient computing and storage resources with fast transmission and powerful processing to satisfy users' service level agreements (SLAs). This paper presents a multi-layered distributed cloud network (MDC) for CPES, with the design of the physical integration of energy systems, a distributed cloud architecture and a hierarchal information structure based on the fifth generation (5G). Furthermore, we present a two-level resource allocation model for cloud network, which aims to decide the location of deploying cloud facilities and dynamically adjust the number of virtual machines (VMs) to deal with the demand variation. We also simplify the model to only one level utilizing scalarization. The simulation shows the proposed model performs effectively compared to centralized solutions.

Original languageEnglish
Title of host publication2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018
PublisherIEEE Computer Society
Pages402-407
Number of pages6
ISBN (Electronic)9781538635933
DOIs
StatePublished - 4 Dec 2018
Event14th IEEE International Conference on Automation Science and Engineering, CASE 2018 - Munich, Germany
Duration: 20 Aug 201824 Aug 2018

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2018-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference14th IEEE International Conference on Automation Science and Engineering, CASE 2018
Country/TerritoryGermany
CityMunich
Period20/08/1824/08/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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