大数据
计算机科学
云计算
块链
数据科学
互联网
软件部署
万维网
计算机安全
数据挖掘
软件工程
操作系统
作者
Joey H. Li,Münür Sacit Herdem,Jatin Nathwani,John Z. Wen
出处
期刊:Energy and AI
[Elsevier]
日期:2022-10-04
卷期号:11: 100208-100208
被引量:171
标识
DOI:10.1016/j.egyai.2022.100208
摘要
Information technologies involving artificial Intelligence, big data, Internet of Things devices and blockchain have been developed and implemented in many engineering fields worldwide. Existing review articles focus on developments and characteristics of individual topics and the associated deployment in the energy sector. These technologies, all based on communication, information, and data analysis, are naturally coherent and integrable. This article reviews the literature and patents in four closely related fields and aims to provide a holistic view of how they are related and their integrability in relation to smart energy management strategies. Artificial intelligence models forecast energy use and load profiles as well as schedule resources to ensure reliable performance and effective utilization of energy resources. Training artificial intelligence models requires immense volumes of data. Utilizing big data systems and data mining enables the discovery of new functions and relationships, which determines the performance of artificial intelligence. Data mining also refines the information; thus, artificial intelligence is trained iteratively with more accurate data. Smart energy management can be further enhanced through advanced digital technologies like Internet of Things and blockchain. An Internet of Things platform containing edge, fog and cloud layers helps connect artificial intelligence to other hardware and software devices and systems. Furthermore, an Internet of Things platform efficiently transmits and stores data, improving access and availability to stakeholders for data mining. Emerging technologies such as blockchain and cryptocurrency facilitate energy trading and can be designed in the cloud layer of an Internet of Things platform to supplement data storage. Providing an efficient and seamless integration of artificial intelligence, big data, and advanced digital technologies will be an important factor in the emerging transition of the energy sector to a lower-carbon system.
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