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Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

Nallapaneni Manoj Kumar, Aneesh A. Chand, Maria Malvoni, Kushal A. Prasad, Kabir A. Mamun, F.R. Islam and Shauhrat S. Chopra
Additional contact information
Nallapaneni Manoj Kumar: School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong
Aneesh A. Chand: School of Engineering and Physics, The University of the South Pacific, Suva, Fiji
Maria Malvoni: School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Zografou, Greece
Kushal A. Prasad: School of Engineering and Physics, The University of the South Pacific, Suva, Fiji
Kabir A. Mamun: School of Engineering and Physics, The University of the South Pacific, Suva, Fiji
F.R. Islam: School of Science and Engineering, University of Sunshine Coast, Sippy Downs, QLD 4556, Australia
Shauhrat S. Chopra: School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong

Energies, 2020, vol. 13, issue 21, 1-42

Abstract: Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability.

Keywords: smart microgrids; modern power system; power infrastructure; distributed energy resources; machine learning; deep learning; Internet of Things; blockchain; electricity system networks; peer to peer network; renewable energy resources; electric vehicle as DER; cybersecurity; smart grid services; resilience; automated services in microgrids; energy Internet (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (28)

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