IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i10p3543-d813944.html
   My bibliography  Save this article

Impact of Forecasting Models Errors in a Peer-to-Peer Energy Sharing Market

Author

Listed:
  • Luis Gomes

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto, 4200-072 Porto, Portugal)

  • Hugo Morais

    (INESC-ID—Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento, Department of Electrical and Computer Engineering, Instituto Superior Técnico—IST, Universidade de Lisboa, 1049-001 Lisboa, Portugal)

  • Calvin Gonçalves

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto, 4200-072 Porto, Portugal)

  • Eduardo Gomes

    (INESC-ID—Instituto de Engenharia de Sistemas e Computadores-Investigação e Desenvolvimento, Department of Electrical and Computer Engineering, Instituto Superior Técnico—IST, Universidade de Lisboa, 1049-001 Lisboa, Portugal
    ITI/LARSyS—Interactive Technologies Institute/Laboratory of Robotics and Engineering Systems, Instituto Superior Técnico—IST, Universidade de Lisboa, 1049-001 Lisboa, Portugal)

  • Lucas Pereira

    (ITI/LARSyS—Interactive Technologies Institute/Laboratory of Robotics and Engineering Systems, Instituto Superior Técnico—IST, Universidade de Lisboa, 1049-001 Lisboa, Portugal)

  • Zita Vale

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto, 4200-072 Porto, Portugal)

Abstract

The use of energy sharing models in smart grids has been widely addressed in the literature. However, feasible technical solutions that can deploy these models into reality, as well as the correct use of energy forecasts are not properly addressed. This paper proposes a simple, yet viable and feasible, solution to deploy energy management systems on the end-user-side in order to enable not only energy forecasting but also a distributed discriminatory-price auction peer-to-peer energy transaction market. This work also analyses the impact of four energy forecasting models on energy transactions: a mathematical model, a support-vector machine model, an eXtreme Gradient Boosting model, and a TabNet model. To test the proposed solution and models, the system was deployed in five small offices and three residential households, achieving a maximum of energy costs reduction of 10.89% within the community, ranging from 0.24% to 57.43% for each individual agent. The results demonstrated the potential of peer-to-peer energy transactions to promote energy cost reductions and enable the validation of auction-based energy transactions and the use of energy forecasting models in today’s buildings and end-users.

Suggested Citation

  • Luis Gomes & Hugo Morais & Calvin Gonçalves & Eduardo Gomes & Lucas Pereira & Zita Vale, 2022. "Impact of Forecasting Models Errors in a Peer-to-Peer Energy Sharing Market," Energies, MDPI, vol. 15(10), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3543-:d:813944
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/10/3543/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/10/3543/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    2. Eugenio Borghini & Cinzia Giannetti & James Flynn & Grazia Todeschini, 2021. "Data-Driven Energy Storage Scheduling to Minimise Peak Demand on Distribution Systems with PV Generation," Energies, MDPI, vol. 14(12), pages 1-22, June.
    3. Chen Zhang & Yong Wang & Tao Yang, 2020. "Iterative Auction for P2P Renewable Energy Trading with Dynamic Energy Storage Management," Energies, MDPI, vol. 13(18), pages 1-20, September.
    4. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    5. Xu, Shuang & Zhao, Yong & Li, Yuanzheng & Zhou, Yue, 2021. "An iterative uniform-price auction mechanism for peer-to-peer energy trading in a community microgrid," Applied Energy, Elsevier, vol. 298(C).
    6. Inês, Campos & Guilherme, Pontes Luz & Esther, Marín-González & Swantje, Gährs & Stephen, Hall & Lars, Holstenkamp, 2020. "Regulatory challenges and opportunities for collective renewable energy prosumers in the EU," Energy Policy, Elsevier, vol. 138(C).
    7. Adamu Sani Yahaya & Nadeem Javaid & Fahad A. Alzahrani & Amjad Rehman & Ibrar Ullah & Affaf Shahid & Muhammad Shafiq, 2020. "Blockchain Based Sustainable Local Energy Trading Considering Home Energy Management and Demurrage Mechanism," Sustainability, MDPI, vol. 12(8), pages 1-28, April.
    8. Ante, L. & Steinmetz, F. & Fiedler, I., 2021. "Blockchain and energy: A bibliometric analysis and review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    9. Yuki Matsuda & Yuto Yamazaki & Hiromu Oki & Yasuhiro Takeda & Daishi Sagawa & Kenji Tanaka, 2021. "Demonstration of Blockchain Based Peer to Peer Energy Trading System with Real-Life Used PHEV and HEMS Charge Control," Energies, MDPI, vol. 14(22), pages 1-12, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Arnob Das & Susmita Datta Peu & Md. Abdul Mannan Akanda & Abu Reza Md. Towfiqul Islam, 2023. "Peer-to-Peer Energy Trading Pricing Mechanisms: Towards a Comprehensive Analysis of Energy and Network Service Pricing (NSP) Mechanisms to Get Sustainable Enviro-Economical Energy Sector," Energies, MDPI, vol. 16(5), pages 1-27, February.
    2. Siripha Junlakarn & Phimsupha Kokchang & Kulyos Audomvongseree, 2022. "Drivers and Challenges of Peer-to-Peer Energy Trading Development in Thailand," Energies, MDPI, vol. 15(3), pages 1-25, February.
    3. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    4. Zheng, Boshen & Wei, Wei & Chen, Yue & Wu, Qiuwei & Mei, Shengwei, 2022. "A peer-to-peer energy trading market embedded with residential shared energy storage units," Applied Energy, Elsevier, vol. 308(C).
    5. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    6. Liu, Jicheng & Sun, Jiakang & Yuan, Hanying & Su, Yihan & Feng, Shuxian & Lu, Chaoran, 2022. "Behavior analysis of photovoltaic-storage-use value chain game evolution in blockchain environment," Energy, Elsevier, vol. 260(C).
    7. Zheyuan Sun & Sara Tavakoli & Kaveh Khalilpour & Alexey Voinov & Jonathan Paul Marshall, 2024. "Barriers to Peer-to-Peer Energy Trading Networks: A Multi-Dimensional PESTLE Analysis," Sustainability, MDPI, vol. 16(4), pages 1-23, February.
    8. Adisorn Leelasantitham & Thammavich Wongsamerchue & Yod Sukamongkol, 2024. "Economic Pricing in Peer-to-Peer Electrical Trading for a Sustainable Electricity Supply Chain Industry in Thailand," Energies, MDPI, vol. 17(5), pages 1-19, March.
    9. Alaa A. F. Husain & Maryam Huda Ahmad Phesal & Mohd Zainal Abidin Ab Kadir & Ungku Anisa Ungku Amirulddin & Abdulhadi H. J. Junaidi, 2021. "A Decade of Transitioning Malaysia toward a High-Solar PV Energy Penetration Nation," Sustainability, MDPI, vol. 13(17), pages 1-16, September.
    10. Lopez, Hector K. & Zilouchian, Ali, 2023. "Peer-to-peer energy trading for photo-voltaic prosumers," Energy, Elsevier, vol. 263(PA).
    11. Liu, Yun & Gao, Yunqiang & Borghetti, Alberto & Li, Yuanzheng & Gooi, Hoay Beng & Sun, Chao & Wu, Ting & Zhu, Jizhong, 2024. "A decentralized approach for time-of-use network utilization pricing in peer-to-peer energy markets," Applied Energy, Elsevier, vol. 361(C).
    12. Filipe Bandeiras & Álvaro Gomes & Mário Gomes & Paulo Coelho, 2023. "Exploring Energy Trading Markets in Smart Grid and Microgrid Systems and Their Implications for Sustainability in Smart Cities," Energies, MDPI, vol. 16(2), pages 1-41, January.
    13. Wicak Ananduta & Sergio Grammatico, 2022. "Equilibrium Seeking and Optimal Selection Algorithms in Peer-to-Peer Energy Markets," Games, MDPI, vol. 13(5), pages 1-13, October.
    14. Boiarkin, Veniamin & Rajarajan, Muttukrishnan & Al-Zaili, Jafar & Asif, Waqar, 2023. "A novel dynamic pricing model for a microgrid of prosumers with photovoltaic systems," Applied Energy, Elsevier, vol. 342(C).
    15. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.
    16. Rodrigues, Stefane Dias & Garcia, Vinicius Jacques, 2023. "Transactive energy in microgrid communities: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    17. Gjorgievski, Vladimir Z. & Cundeva, Snezana & Markovska, Natasa & Georghiou, George E., 2022. "Virtual net-billing: A fair energy sharing method for collective self-consumption," Energy, Elsevier, vol. 254(PB).
    18. Roth, Tamara & Utz, Manuel & Baumgarte, Felix & Rieger, Alexander & Sedlmeir, Johannes & Strüker, Jens, 2022. "Electricity powered by blockchain: A review with a European perspective," Applied Energy, Elsevier, vol. 325(C).
    19. Meritxell Domènech Monfort & César De Jesús & Natapon Wanapinit & Niklas Hartmann, 2022. "A Review of Peer-to-Peer Energy Trading with Standard Terminology Proposal and a Techno-Economic Characterisation Matrix," Energies, MDPI, vol. 15(23), pages 1-29, November.
    20. Tsaousoglou, Georgios & Ellinas, Petros & Varvarigos, Emmanouel, 2023. "Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control," Applied Energy, Elsevier, vol. 343(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3543-:d:813944. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.