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Blockchain Technology Applied to Energy Demand Response Service Tracking and Data Sharing

Author

Listed:
  • Alexandre Lucas

    (European Commission, Joint Research Centre (JRC), Via E. Fermi 2749, I-21027 Ispra, Italy)

  • Dimitrios Geneiatakis

    (European Commission, Joint Research Centre (JRC), Via E. Fermi 2749, I-21027 Ispra, Italy)

  • Yannis Soupionis

    (European Commission, Joint Research Centre (JRC), Via E. Fermi 2749, I-21027 Ispra, Italy)

  • Igor Nai-Fovino

    (European Commission, Joint Research Centre (JRC), Via E. Fermi 2749, I-21027 Ispra, Italy)

  • Evangelos Kotsakis

    (European Commission, Joint Research Centre (JRC), Via E. Fermi 2749, I-21027 Ispra, Italy)

Abstract

Demand response (DR) services have the potential to enable large penetration of renewable energy by adjusting load consumption, thus providing balancing support to the grid. The success of such load flexibility provided by industry, communities, or prosumers and its integration in electricity markets, will depend on a redesign and adaptation of the current interactions between participants. New challenges are, however, bound to appear with the large scale contribution of smaller assets to flexibility, including, among others, the dispatch coordination, the validation of delivery of the DR provision, and the corresponding settlement of contracts, while assuring secured data access among interested parties. In this study we applied distributed ledger (DLT)/blockchain technology to securely track DR provision, focusing on the validation aspect, assuring data integrity, origin, fast registry, and sharing within a permissioned system, between all relevant parties (including transmission system operators (TSOs), aggregators, distribution system operators (DSOs), balance responsible parties (BRP), and prosumers). We propose a framework for DR registry and implemented it as a proof of concept on Hyperledger Fabric, using real assets in a laboratory environment, in order to study its feasibility and performance. The lab set up includes a 450 kW energy storage system, scheduled to provide DR services, upon a system operator request and the corresponding validations and verifications are done, followed by the publication on a blockchain. Results show the end to end execution time remained below 1 s, when below 32 requests/sec. The smart contract memory utilization did not surpass 1% for both active and passive nodes and the peer CPU utilization, remained below 5% in all cases simulated (3, 10, and 28 nodes). Smart Contract CPU utilization remained stable, below 1% in all cases. The performance of the implementation showed scalable results, which enables real world adoption of DLT in supporting the development of flexibility markets, with the advantages of blockchain technology.

Suggested Citation

  • Alexandre Lucas & Dimitrios Geneiatakis & Yannis Soupionis & Igor Nai-Fovino & Evangelos Kotsakis, 2021. "Blockchain Technology Applied to Energy Demand Response Service Tracking and Data Sharing," Energies, MDPI, vol. 14(7), pages 1-17, March.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1881-:d:526106
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    References listed on IDEAS

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    1. Mengelkamp, Esther & Gärttner, Johannes & Rock, Kerstin & Kessler, Scott & Orsini, Lawrence & Weinhardt, Christof, 2018. "Designing microgrid energy markets," Applied Energy, Elsevier, vol. 210(C), pages 870-880.
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    3. Seong-Kyu Kim & Jun-Ho Huh, 2018. "A Study on the Improvement of Smart Grid Security Performance and Blockchain Smart Grid Perspective," Energies, MDPI, vol. 11(8), pages 1-22, July.
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    2. Loup-Noé Lévy & Jérémie Bosom & Guillaume Guerard & Soufian Ben Amor & Marc Bui & Hai Tran, 2022. "DevOps Model Appproach for Monitoring Smart Energy Systems," Energies, MDPI, vol. 15(15), pages 1-27, July.
    3. Hani Alshahrani & Noman Islam & Darakhshan Syed & Adel Sulaiman & Mana Saleh Al Reshan & Khairan Rajab & Asadullah Shaikh & Jaweed Shuja-Uddin & Aadar Soomro, 2023. "Sustainability in Blockchain: A Systematic Literature Review on Scalability and Power Consumption Issues," Energies, MDPI, vol. 16(3), pages 1-24, February.
    4. Marco Vittorio Ecclesia & João Santos & Paul E. Brockway & Tiago Domingos, 2022. "A Comprehensive Societal Energy Return on Investment Study of Portugal Reveals a Low but Stable Value," Energies, MDPI, vol. 15(10), pages 1-22, May.
    5. Yue Wu & Junxiang Li & Jin Gao, 2021. "Real-Time Bidding Model of Cryptocurrency Energy Trading Platform," Energies, MDPI, vol. 14(21), pages 1-14, November.

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