Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids

The deregulation and decentralization of the energy market have resulted in a proliferation of distributed generation that participates in energy trading as prosumers. In peer-to-peer (P2P) trading of energy within the microgrid (MG), the peers can trade energy without the need for an intermediary....

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Main Authors: Veerasamy, Veerapandiyan, Hu, Zhijian, Qiu, Haifeng, Murshid, Shadab, Gooi, Hoay Beng, Nguyen, Hung Dinh
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/173305
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1733052024-01-23T07:34:42Z Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids Veerasamy, Veerapandiyan Hu, Zhijian Qiu, Haifeng Murshid, Shadab Gooi, Hoay Beng Nguyen, Hung Dinh School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Federated Learning Differential Privacy The deregulation and decentralization of the energy market have resulted in a proliferation of distributed generation that participates in energy trading as prosumers. In peer-to-peer (P2P) trading of energy within the microgrid (MG), the peers can trade energy without the need for an intermediary. Blockchain technology is devised to assure the security and resilience of the system's P2P trading against adversarial attacks. The large number of renewable prosumers who participate in trading raises the MG system's oscillation frequency. To regulate the system frequency during trading, a distributed-based federated learned fractional-order recurrent neural network (FL-FORNN) adaptive controller is proposed. The control system is a crucial component of MGs in order to ensure stable performance. To aggregate the network weights, the proposed FL-based controller frequently communicates with the cloud server. To avoid the privacy threat during this case, we further propose to integrate FL with local differential privacy (LDP) to secure against the false data injection attack from the eavesdropper. To validate, the MG model is implemented in OPAL-RT with its resilient controller. The P2P trading of energy in the blockchain is executed in Raspberry Pis (RPis) based on the numerous prosumers/consumers participating in the trading. Then, the power information from the tertiary control implemented in RPis is communicated with the MG secondary frequency controller by interfacing using the user datagram protocol. The proposed work is realized for the MG considering four prosumers and three consumers, and the resiliency of the controller is authenticated with case studies. The results divulge that the LDP of the proposed controller can provide a robust and secure solution of MGs with P2P trading, even in the presence of adversarial attacks. Energy Market Authority (EMA) Ministry of Education (MOE) National Research Foundation (NRF) This research is supported by the National Research Foundation of Singapore, and the Energy Market Authority, under its Energy Programme EP Award EMA-EP004-EKJGC-0003, Ministry of Education Singapore under its Award AcRF TIER 1 RG60/22, and Intra-CREATE Seed Fund Award NRF2022-ITS010-0005. 2024-01-23T07:34:42Z 2024-01-23T07:34:42Z 2024 Journal Article Veerasamy, V., Hu, Z., Qiu, H., Murshid, S., Gooi, H. B. & Nguyen, H. D. (2024). Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids. Applied Energy, 353, 122107-. https://dx.doi.org/10.1016/j.apenergy.2023.122107 0306-2619 https://hdl.handle.net/10356/173305 10.1016/j.apenergy.2023.122107 2-s2.0-85174165527 353 122107 en EMA-EP004-EKJGC-0003 RG60/22 NRF2022-ITS010-0005 Applied Energy © 2023 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Federated Learning
Differential Privacy
spellingShingle Engineering::Electrical and electronic engineering
Federated Learning
Differential Privacy
Veerasamy, Veerapandiyan
Hu, Zhijian
Qiu, Haifeng
Murshid, Shadab
Gooi, Hoay Beng
Nguyen, Hung Dinh
Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids
description The deregulation and decentralization of the energy market have resulted in a proliferation of distributed generation that participates in energy trading as prosumers. In peer-to-peer (P2P) trading of energy within the microgrid (MG), the peers can trade energy without the need for an intermediary. Blockchain technology is devised to assure the security and resilience of the system's P2P trading against adversarial attacks. The large number of renewable prosumers who participate in trading raises the MG system's oscillation frequency. To regulate the system frequency during trading, a distributed-based federated learned fractional-order recurrent neural network (FL-FORNN) adaptive controller is proposed. The control system is a crucial component of MGs in order to ensure stable performance. To aggregate the network weights, the proposed FL-based controller frequently communicates with the cloud server. To avoid the privacy threat during this case, we further propose to integrate FL with local differential privacy (LDP) to secure against the false data injection attack from the eavesdropper. To validate, the MG model is implemented in OPAL-RT with its resilient controller. The P2P trading of energy in the blockchain is executed in Raspberry Pis (RPis) based on the numerous prosumers/consumers participating in the trading. Then, the power information from the tertiary control implemented in RPis is communicated with the MG secondary frequency controller by interfacing using the user datagram protocol. The proposed work is realized for the MG considering four prosumers and three consumers, and the resiliency of the controller is authenticated with case studies. The results divulge that the LDP of the proposed controller can provide a robust and secure solution of MGs with P2P trading, even in the presence of adversarial attacks.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Veerasamy, Veerapandiyan
Hu, Zhijian
Qiu, Haifeng
Murshid, Shadab
Gooi, Hoay Beng
Nguyen, Hung Dinh
format Article
author Veerasamy, Veerapandiyan
Hu, Zhijian
Qiu, Haifeng
Murshid, Shadab
Gooi, Hoay Beng
Nguyen, Hung Dinh
author_sort Veerasamy, Veerapandiyan
title Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids
title_short Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids
title_full Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids
title_fullStr Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids
title_full_unstemmed Blockchain-enabled peer-to-peer energy trading and resilient control of microgrids
title_sort blockchain-enabled peer-to-peer energy trading and resilient control of microgrids
publishDate 2024
url https://hdl.handle.net/10356/173305
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