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Title: Distributed foresighted energy management in smart-grid-powered cellular networks
Authors: Zhang, Xinruo
Nakhai, Mohammad R.
Zheng, Gan
Lambotharan, Sangarapillai
Chambers, Jonathon
Issue Date: 2019
Publisher: © IEEE
Citation: ZHANG, X. ... et al, 2019. Distributed foresighted energy management in smart-grid-powered cellular networks. IEEE Transactions on Vehicular Technology, doi:10.1109/TVT.2019.2899464.
Abstract: This paper studies energy management in a smart grid-powered cellular network consisting of an independent system operator (ISO) and multiple geographically distributed aggregators. The aggregators have energy storage devices and can purchase energy from the electric grid via the ISO to serve their users. To account for the uncertainty of the renewable energy supply as well as the impacts of multiple aggregators on the electric grid and energy prices, a foresighted strategy combined with the adaptive ϵ -greedy method is developed for the aggregators to distributively and adaptively minimize the long-term overall cost of the system based on the ahead-of-time decision making of the storage pre-charging amount. Simulation results validate that the proposed strategy surpasses a recent learning-based storage management design and a myopic design.
Description: This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
Sponsor: This work was supported in part by the UK EPSRC under Grant EP/N007840/1 and in part by the Leverhulme Trust under Grant RPG-2017-129.
Version: Published
DOI: 10.1109/TVT.2019.2899464
URI: https://dspace.lboro.ac.uk/2134/36952
Publisher Link: https://doi.org/10.1109/TVT.2019.2899464
ISSN: 0018-9545
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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