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Enhancing dynamic energy network management using a multiagent cloud-fog structure

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  • Haghnegahdar, Lida
  • Chen, Yu
  • Wang, Yong

Abstract

Smart Grid benefits from information and communications technology (ICT) to integrate data from different sources across the network. The growing market for electric vehicles (EV) and electric devices is increasing energy demand. To manage a large amount of complex intelligent equipment, EV charging and discharging, and data-intensive devices, a reliable modern smart grid with a service-oriented, secure, efficient, and cost-effective system is compelling. Cloud computing is a promising approach to achieve that objective as monitoring power grid data flow and data center management are the key. This paper proposes an optimization model for energy management within the power cloud. Our energy system model enables accessible services to computing resources and real-time data stream processing within an integrated environment. Using digital technology, the proper implementation of our model reduces costs and energy consumption and improves the smart grid reliability for customers and energy providers in a distributed manner. This paper presents the implementation of a three-procedure optimization algorithm within a novel Multi-Agent Cloud-fog Structure (MACS) to meet the requirements raised by smart grid communication and distribution. Our model promotes reliable energy consumption adjustments by end-users who can choose power supplied by solar, wind, geothermal, biomass, or other renewable sources or from non-renewable sources in ways that reveal opportunities for demand-supply balance and energy saving.

Suggested Citation

  • Haghnegahdar, Lida & Chen, Yu & Wang, Yong, 2022. "Enhancing dynamic energy network management using a multiagent cloud-fog structure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    • Handle: RePEc:eee:rensus:v:162:y:2022:i:c:s1364032122003458
    DOI: 10.1016/j.rser.2022.112439
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Hongyan & Gao, Shuaizhi & Zhou, Peng, 2023. "Role of digitalization in energy storage technological innovation: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).

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