Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156602
Title: FogChain - constructing a blockchain-based power trading system
Authors: Lee, Larry Ken Ann
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Lee, L. K. A. (2022). FogChain - constructing a blockchain-based power trading system. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156602
Project: FogChain: A Blockchain-Based Peer-to-Peer Solar Power Trading System Powered by Fog AI / 10.1109/JIOT.2021.3109057
Abstract: As the world move towards sustainable energy, microgrids (self-sufficient, clean, decentralized energy system) has an accelerated CAGR (Compound Annual Growth Rate) of 12.86% which dictates that the market size will increase by USD 15 billion in the next three years. This market opportunity demands for new and novel solutions to regulate the operations of the many decentralized microgrids. Specifically, facilitating the transfer of energy and money among microgrid participants. FogChain, an intelligent microgrid management system powered by Blockchain and Fog Computing, aims to become a key market player in this segment. The development of Fog Chain has been in progress by a broader team since 2020. FogChain aims to further develop and validate its core functionalities, energy trading and microgrids management, while conducting realistic demonstrations for investors to provide additional funding to realize the project. Further validation of the FogChain system relies on the construction of simulated microgrids (Digital Twin). The microgrids simulation developed in this paper would go on to provide the FogChain team a realistic virtual testing ground to conduct further experiments and tests. As the project move towards real-world deployment, the importance of the Digital Twin System will continue to grow and serve as the key execution layer between FogChain and the physical world.
URI: https://hdl.handle.net/10356/156602
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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