SynergyGrids: blockchain-supported distributed microgrid energy trading

Growing intelligent cities is witnessing an increasing amount of local energy generation through renewable energy resources. Energy trade among the local energy generators ( aka prosumers) and consumers can reduce the energy consumption cost and also reduce the dependency on conventional energy reso...

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Bibliographic Details
Published in:Peer-to-peer networking and applications 2022-03, Vol.15 (2), p.884-900
Main Authors: Aloqaily, Moayad, Bouachir, Ouns, Özkasap, Öznur, Ali, Faizan Safdar
Format: Article
Language:English
Subjects:
Communications Engineering
Computer Communication Networks
Consumers
Cryptography
Distributed generation
Electrical loads
Energy consumption
Energy costs
Energy resources
Energy sources
Engineering
Hybrid systems
Information Systems and Communication Service
Networks
Signal,Image and Speech Processing
Special Issue on Blockchain for Peer-to-Peer Computing
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Summary:Growing intelligent cities is witnessing an increasing amount of local energy generation through renewable energy resources. Energy trade among the local energy generators ( aka prosumers) and consumers can reduce the energy consumption cost and also reduce the dependency on conventional energy resources, not to mention the environmental, economic, and societal benefits. However, these local energy sources might not be enough to fulfill energy consumption demands. A hybrid approach, where consumers can buy energy from both prosumers (that generate energy) and also from prosumer of other locations, is essential. A centralized system can be used to manage this energy trading that faces several security issues and increase centralized development cost. In this paper, a hybrid energy trading system coupled with a smart contract named SynergyGrids has been proposed as a solution, that reduces the average cost of energy and load over the utility grids. To the best of our knowledge, this work is the first attempt to create a hybrid energy trading platform over the smart contract for energy demand prediction. An hourly energy data set has been utilized for testing and validation purposes. The trading system shows 17.8% decrease in energy cost for consumers and 76.4% decrease in load over utility grids when compared with its counterparts.
ISSN:1936-6442
1936-6450
DOI:10.1007/s12083-021-01199-y