Secure and Efficient Peer-to-Peer Energy Trading: A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making

E. Eslam Mofreh Attia Ali Ganb; Phuong H. Nguyen; J.K. (Koen) Kok

doi:10.1109/EEEIC/ICPSEurope61470.2024.10751115

Secure and Efficient Peer-to-Peer Energy Trading: A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making

E. Eslam Mofreh Attia Ali Ganb, Phuong H. Nguyen, J.K. (Koen) Kok

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

Abstract

This paper introduces an innovative simulation platform designed to reshape decentralized decision-making processes. By simulating real-world scenarios within an edge computing environment, the platform provides a way to study decentralized decision-making. Leveraging a central Communication Coordinator facilitates dynamic interactions among edge devices, with a particular focus on their application in peer-to-peer energy trading. The platform enables seamless processes, including registration, trading initiation, negotiation, and transaction confirmation. Rigorous evaluations, centered around a peer-to-peer energy trading case study, highlight the platform's effectiveness in securing, standardizing, and optimizing communication. Notably, our findings reveal significant improvements in data integrity, communication efficiency, and overall performance. This research represents a significant leap forward in comprehending decentralized decision-making dynamics and holds promise for diverse applications beyond the realm of energy trading.

Original language	English
Title of host publication	2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
Editors	Zbigniew Leonowicz, Erika Stracqualursi
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	6
ISBN (Electronic)	979-8-3503-5518-5
DOIs	https://doi.org/10.1109/EEEIC/ICPSEurope61470.2024.10751115
Publication status	Published - 20 Nov 2024
Event	24th IEEE International Conference on Environment and Electrical Engineering, 8th I&CPS Industrial and Commercial Power Systems Europe, EEEIC / I&CPS Europe - Rome, Italy Duration: 17 Jun 2024 → 20 Jun 2024

Conference

Conference	24th IEEE International Conference on Environment and Electrical Engineering, 8th I&CPS Industrial and Commercial Power Systems Europe, EEEIC / I&CPS Europe
Country/Territory	Italy
City	Rome
Period	17/06/24 → 20/06/24

Funding

This research was funded by the research program \"Mega-Mind-Measuring, Gathering, Mining and Integrating Data for Selfmanagement in the Edge of the Electricity System\", (partly) financed by the Dutch Research Council (NWO) through the Perspectief program under number P19-25.

Funders	Funder number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	P19-25

Keywords

Decentralized Energy Systems
Edge Computing
Peer-to-Peer Trading
Secure Data Sharing
Semantic Interoperability
Smart Grid
Standardized Data Sharing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/EEEIC/ICPSEurope61470.2024.10751115

Cite this

Eslam Mofreh Attia Ali Ganb, E., Nguyen, P. H., & Kok, J. K. (2024). Secure and Efficient Peer-to-Peer Energy Trading: A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making. In Z. Leonowicz, & E. Stracqualursi (Eds.), 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) Article 10751115 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EEEIC/ICPSEurope61470.2024.10751115

Eslam Mofreh Attia Ali Ganb, E. ; Nguyen, Phuong H. ; Kok, J.K. (Koen). / Secure and Efficient Peer-to-Peer Energy Trading : A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making. 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). editor / Zbigniew Leonowicz ; Erika Stracqualursi. Institute of Electrical and Electronics Engineers, 2024.

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abstract = "This paper introduces an innovative simulation platform designed to reshape decentralized decision-making processes. By simulating real-world scenarios within an edge computing environment, the platform provides a way to study decentralized decision-making. Leveraging a central Communication Coordinator facilitates dynamic interactions among edge devices, with a particular focus on their application in peer-to-peer energy trading. The platform enables seamless processes, including registration, trading initiation, negotiation, and transaction confirmation. Rigorous evaluations, centered around a peer-to-peer energy trading case study, highlight the platform's effectiveness in securing, standardizing, and optimizing communication. Notably, our findings reveal significant improvements in data integrity, communication efficiency, and overall performance. This research represents a significant leap forward in comprehending decentralized decision-making dynamics and holds promise for diverse applications beyond the realm of energy trading.",

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author = "{Eslam Mofreh Attia Ali Ganb}, E. and Nguyen, {Phuong H.} and Kok, {J.K. (Koen)}",

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Eslam Mofreh Attia Ali Ganb, E , Nguyen, PH & Kok, JK 2024, Secure and Efficient Peer-to-Peer Energy Trading: A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making. in Z Leonowicz & E Stracqualursi (eds), 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)., 10751115, Institute of Electrical and Electronics Engineers, 24th IEEE International Conference on Environment and Electrical Engineering, 8th I&CPS Industrial and Commercial Power Systems Europe, EEEIC / I&CPS Europe, Rome, Italy, 17/06/24. https://doi.org/10.1109/EEEIC/ICPSEurope61470.2024.10751115

Secure and Efficient Peer-to-Peer Energy Trading: A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making. / Eslam Mofreh Attia Ali Ganb, E.; Nguyen, Phuong H.; Kok, J.K. (Koen).
2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). ed. / Zbigniew Leonowicz; Erika Stracqualursi. Institute of Electrical and Electronics Engineers, 2024. 10751115.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

TY - GEN

T1 - Secure and Efficient Peer-to-Peer Energy Trading

T2 - 24th IEEE International Conference on Environment and Electrical Engineering, 8th I&CPS Industrial and Commercial Power Systems Europe, EEEIC / I&CPS Europe

AU - Eslam Mofreh Attia Ali Ganb, E.

AU - Nguyen, Phuong H.

AU - Kok, J.K. (Koen)

PY - 2024/11/20

Y1 - 2024/11/20

N2 - This paper introduces an innovative simulation platform designed to reshape decentralized decision-making processes. By simulating real-world scenarios within an edge computing environment, the platform provides a way to study decentralized decision-making. Leveraging a central Communication Coordinator facilitates dynamic interactions among edge devices, with a particular focus on their application in peer-to-peer energy trading. The platform enables seamless processes, including registration, trading initiation, negotiation, and transaction confirmation. Rigorous evaluations, centered around a peer-to-peer energy trading case study, highlight the platform's effectiveness in securing, standardizing, and optimizing communication. Notably, our findings reveal significant improvements in data integrity, communication efficiency, and overall performance. This research represents a significant leap forward in comprehending decentralized decision-making dynamics and holds promise for diverse applications beyond the realm of energy trading.

AB - This paper introduces an innovative simulation platform designed to reshape decentralized decision-making processes. By simulating real-world scenarios within an edge computing environment, the platform provides a way to study decentralized decision-making. Leveraging a central Communication Coordinator facilitates dynamic interactions among edge devices, with a particular focus on their application in peer-to-peer energy trading. The platform enables seamless processes, including registration, trading initiation, negotiation, and transaction confirmation. Rigorous evaluations, centered around a peer-to-peer energy trading case study, highlight the platform's effectiveness in securing, standardizing, and optimizing communication. Notably, our findings reveal significant improvements in data integrity, communication efficiency, and overall performance. This research represents a significant leap forward in comprehending decentralized decision-making dynamics and holds promise for diverse applications beyond the realm of energy trading.

KW - Decentralized Energy Systems

KW - Edge Computing

KW - Peer-to-Peer Trading

KW - Secure Data Sharing

KW - Semantic Interoperability

KW - Smart Grid

KW - Standardized Data Sharing

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U2 - 10.1109/EEEIC/ICPSEurope61470.2024.10751115

DO - 10.1109/EEEIC/ICPSEurope61470.2024.10751115

M3 - Conference contribution

BT - 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

A2 - Leonowicz, Zbigniew

A2 - Stracqualursi, Erika

PB - Institute of Electrical and Electronics Engineers

Y2 - 17 June 2024 through 20 June 2024

ER -

Eslam Mofreh Attia Ali Ganb E , Nguyen PH , Kok JK. Secure and Efficient Peer-to-Peer Energy Trading: A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making. In Leonowicz Z, Stracqualursi E, editors, 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). Institute of Electrical and Electronics Engineers. 2024. 10751115 doi: 10.1109/EEEIC/ICPSEurope61470.2024.10751115

Secure and Efficient Peer-to-Peer Energy Trading: A Case Study on Edge Computing Simulation Platform for Decentralized Decision Making

Abstract

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Keywords

UN SDGs

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