Researcher:
Ali, Faizan Safdar

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Master Student

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Faizan Safdar

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Ali

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Ali, Faizan Safdar

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Now showing 1 - 6 of 6
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    Publication
    Joulin: blockchain-based P2P energy trading using smart contracts
    (IEEE, 2020) N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Computer Engineering; N/A; Department of Computer Engineering; Department of Computer Engineering; Perk, Berrak; Bayraktaroğlu, Can; Doğu, Engin Deniz; Ali, Faizan Safdar; Özkasap, Öznur; Undergraduate Student; Undergraduate Student; Undergraduate Student; Master Student; Faculty Member; College of Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; N/A; N/A; 113507
    As a decentralized immutable ledger where several trustless peers can reach consensus with each other without the need of any trusted third party, blockchain technology fits perfectly with the peer-to-peer (P2P) energy trading paradigm. In this paper, we propose, design and analyze a marketplace for energy trading based on smart contracts on the blockchain. The proposed system named Joulin serves as a competitive and efficient marketplace where peers can both produce, buy and sell energy depending on their needs. As a proof-of-concept, we developed the prototype of the Joulin system using Ethereum blockchain. Our results, in terms of usability, flexibility and resiliency, demonstrate the potential to achieve an easily extendable and reliable system with low transaction costs. Low Ethereum gas costs and quick response times demonstrate usability. Our smart contracts have also been tested with security tools to ensure that they are not vulnerable to outside manipulations.
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    Publication
    Synergychain: blockchain-assisted adaptive cyber-physical p2p energy trading
    (Ieee-Inst Electrical Electronics Engineers Inc, 2021) Bouachir, Ouns; Aloqaily, Moayad; N/A; Department of Computer Engineering; Department of Computer Engineering; Ali, Faizan Safdar; Özkasap, Öznur; Master Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 113507
    Industrial investments into distributed energy resource technologies are increasing and playing a pivotal role in the global transactive energy, as part of a wider drive to provide a clean and stable source of energy. The management of prosumers, which consume and as well as generate energy, with heterogeneous energy sources is critical for sustainable and efficient energy trading procedures. This article proposes a blockchain-assisted adaptive model, namely SynergyChain, for improving the scalability and decentralization of the prosumer grouping mechanism in the context of peer-to-peer energy trading. Smart contracts are used for storing the transaction information and for the creation of the prosumer groups. SynergyChain integrates a reinforcement learning module to further improve the overall system performance and profitability by creating a self-adaptive grouping technique. The proposed SynergyChain is developed using Python and Solidity and has been tested using Ethereum test nets. The comprehensive analysis using the hourly energy consumption dataset shows a 39.7% improvement in the performance and scalability of the system as compared to the centralized systems. The evaluation results confirm that SynergyChain can reduce the request completion time along with an 18.3% improvement in the overall profitability of the system as compared to its counterparts.
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    Publication
    Blockchain-assisted decentralized virtual prosumer grouping for P2P energy trading
    (Ieee Computer Soc, 2020) Aloqaily, Moayad; Bouachir, Ouns; N/A; Department of Computer Engineering; Department of Computer Engineering; Ali, Faizan Safdar; Özkasap, Öznur; Master Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 113507
    Energy trading systems have revolutionized by taking advantage of energy users who produce surplus energy. In the cyberphysical energy sharing systems, the participation of such consumers who can also sell their residuum energy for profit, namely prosumers, is critical for the sustainable and efficient energy sharing procedure and requires improved prosumer management. The idea of grouping the prosumers for better profits is a promising approach for prosumer management which is currently carried out in centralized manner; that face trust, security and scalability issues. Hence, a strong tool that can protect the prosumer privacy; log the changes for audit purposes and eventually improve the performance of the system is necessary. This paper proposes a blockchain-assisted approach using smart contracts for improved scalability and decentralization of the prosumer grouping mechanism in the context of P2P energy trading. The results show around 38.7% improvement in the performance and scalability of the system.
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    PublicationOpen Access
    SynergyGrids: blockchain-supported distributed microgrid energy trading
    (Springer, 2021) Aloqaily, Moayad; Bouachir, Ouns; Department of Computer Engineering; Department of Computer Engineering; Özkasap, Öznur; Ali, Faizan Safdar; Faculty Member; College of Engineering; Graduate School of Sciences and Engineering; 113507; N/A
    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.
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    PublicationOpen Access
    FederatedGrids: federated learning and blockchain-assisted P2P energy sharing
    (Institute of Electrical and Electronics Engineers (IEEE), 2022) Aloqaily, Moayad; Bouachir, Ouns; Department of Computer Engineering; Department of Computer Engineering; Özkasap, Öznur; Ali, Faizan Safdar; Faculty Member; College of Engineering; Graduate School of Sciences and Engineering; 113507; N/A
    Peer-to-Peer (P2P) energy trading platforms envisioned energy sectors to satisfy the increasing demand for energy. The vision of this paper is not only to trade energy but also to have part of it being shared. Therefore, this paper presents FederatedGrids which is a P2P energy trading and sharing platform inside and across microgrids. Energy sharing allows exchanging energy between the categories of consumers and prosumers in return for future benefits. FederatedGrids platform uses blockchain and federated learning to enable autonomous activities while providing trust and privacy among all participants. Indeed, based on various smart contracts using federated learning, FederatedGrids calculates a prediction of the future energy production and demand allowing the system to autonomously switch between trading and sharing, and enabling the prosumers to make decisions related to their participation in the energy sharing process. Up to our knowledge, this work is the first attempt to create a hybrid energy trading and sharing platform, with the real sharing meaning, and that uses federated learning over the smart contract for energy demand prediction. The experimental results showed a 17.8% decrease in energy cost for consumers and a 76.4% decrease in load over utility grids.
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    PublicationOpen Access
    Cyberphysical blockchain-enabled peer-to-peer energy trading
    (Institute of Electrical and Electronics Engineers (IEEE), 2020) Aloqaily, Moayad; Alfandi, Omar; N/A; Department of Computer Engineering; Department of Computer Engineering; Ali, Faizan Safdar; Özkasap, Öznur; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 113507
    Scalability and security problems with centralized architecture models in cyberphysical systems have provided opportunities for blockchain-based distributed models. A decentralized energy-trading system takes advantage of various sources and effectively coordinates the energy to ensure the optimal utilization of available resources. Three blockchainbased energy-trading models are proposed to overcome the technical challenges and market barriers as well as enhance the adoption of this disruptive technology.