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Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review

Hua, Weiqi, Chen, Ying, Qadrdan, Meysam, Jiang, Jing, Sun, Hongjian and Wu, Jianzhong 2022. Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review. Renewable and Sustainable Energy Reviews 161 , 112308. 10.1016/j.rser.2022.112308

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Abstract

Governments’ net zero emission target aims at increasing the share of renewable energy sources as well as influencing the behaviours of consumers to support the cost-effective balancing of energy supply and demand. These will be achieved by the advanced information and control infrastructures of smart grids which allow the interoperability among various stakeholders. Under this circumstance, increasing number of consumers produce, store, and consume energy, giving them a new role of prosumers. The integration of prosumers and accommodation of incurred bidirectional flows of energy and information rely on two key factors: flexible structures of energy markets and intelligent operations of power systems. The blockchain and artificial intelligence (AI) are innovative technologies to fulfil these two factors, by which the blockchain provides decentralised trading platforms for energy markets and the AI supports the optimal operational control of power systems. This paper attempts to address how to incorporate the blockchain and AI in the smart grids for facilitating prosumers to participate in energy markets. To achieve this objective, first, this paper reviews how policy designs price carbon emissions caused by the fossil-fuel based generation so as to facilitate the integration of prosumers with renewable energy sources. Second, the potential structures of energy markets with the support of the blockchain technologies are discussed. Last, how to apply the AI for enhancing the state monitoring and decision making during the operations of power systems is introduced.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Additional Information: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Publisher: Elsevier
ISSN: 1364-0321
Date of First Compliant Deposit: 16 May 2022
Date of Acceptance: 20 February 2022
Last Modified: 16 May 2022 09:45
URI: https://orca.cardiff.ac.uk/id/eprint/149628

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