IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v222y2018icp993-1022.html
   My bibliography  Save this article

Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework

Author

Listed:
  • Zhou, Yue
  • Wu, Jianzhong
  • Long, Chao

Abstract

Peer-to-peer (P2P) energy sharing involves novel technologies and business models at the demand-side of power systems, which is able to manage the increasing connection of distributed energy resources (DERs). In P2P energy sharing, prosumers directly trade energy with each other to achieve a win-win outcome. From the perspectives of power systems, P2P energy sharing has the potential to facilitate local energy balance and self-sufficiency. A systematic index system was developed to evaluate the performance of various P2P energy sharing mechanisms based on a multiagent-based simulation framework. The simulation framework is composed of three types of agents and three corresponding models. Two techniques, i.e. step length control and learning process involvement, and a last-defence mechanism were proposed to facilitate the convergence of simulation and deal with the divergence. The evaluation indexes include three economic indexes, i.e. value tapping, participation willing and equality, and three technical indexes, i.e. energy balance, power flatness and self-sufficiency. They are normalised and further synthesized to reflect the overall performance. The proposed methods were applied to simulate and evaluate three existing P2P energy sharing mechanisms, i.e. the supply and demand ratio (SDR), mid-market rate (MMR) and bill sharing (BS), for residential customers in current and future scenarios of Great Britain. Simulation results showed that both of the step length control and learning process involvement techniques improve the performance of P2P energy sharing mechanisms with moderate ramping/learning rates. The results also showed that P2P energy sharing has the potential to bring both economic and technical benefits for Great Britain. In terms of the overall performance, the SDR mechanism outperforms all the other mechanisms, and the MMR mechanism has good performance when with moderate PV penetration levels. The BS mechanism performs at the similar level as the conventional paradigm. The conclusion on the mechanism performance is not sensitive to season factors, day types and retail price schemes.

Suggested Citation

  • Zhou, Yue & Wu, Jianzhong & Long, Chao, 2018. "Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework," Applied Energy, Elsevier, vol. 222(C), pages 993-1022.
  • Handle: RePEc:eee:appene:v:222:y:2018:i:c:p:993-1022
    DOI: 10.1016/j.apenergy.2018.02.089
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918302149
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2018.02.089?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dagoumas, Athanasios S. & Polemis, Michael L., 2017. "An integrated model for assessing electricity retailer’s profitability with demand response," Applied Energy, Elsevier, vol. 198(C), pages 49-64.
    2. Nojavan, Sayyad & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2017. "Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program," Applied Energy, Elsevier, vol. 187(C), pages 449-464.
    3. Sikorski, Janusz J. & Haughton, Joy & Kraft, Markus, 2017. "Blockchain technology in the chemical industry: Machine-to-machine electricity market," Applied Energy, Elsevier, vol. 195(C), pages 234-246.
    4. Wang, Mingshen & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qi, Yan, 2017. "Active power regulation for large-scale wind farms through an efficient power plant model of electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1673-1683.
    5. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J. & Martín, F., 2016. "Optimal planning and operation of aggregated distributed energy resources with market participation," Applied Energy, Elsevier, vol. 182(C), pages 340-357.
    6. Meng, Jian & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qu, Bo, 2016. "Dynamic frequency response from electric vehicles considering travelling behavior in the Great Britain power system," Applied Energy, Elsevier, vol. 162(C), pages 966-979.
    7. Eid, Cherrelle & Codani, Paul & Perez, Yannick & Reneses, Javier & Hakvoort, Rudi, 2016. "Managing electric flexibility from Distributed Energy Resources: A review of incentives for market design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 237-247.
    8. Jordehi, A. Rezaee, 2015. "Particle swarm optimisation (PSO) for allocation of FACTS devices in electric transmission systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1260-1267.
    9. Cherrelle Eid & Paul Codani & Yannick Perez & Javier Reneses & Rudi Hakvoort, 2016. "Managing electric flexibility from Distributed Energy Resources: A review of incentives for market design," Post-Print hal-01792419, HAL.
    10. Rae, Callum & Bradley, Fiona, 2012. "Energy autonomy in sustainable communities—A review of key issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(9), pages 6497-6506.
    11. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
    12. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    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. Pedro Faria & João Spínola & Zita Vale, 2018. "Reschedule of Distributed Energy Resources by an Aggregator for Market Participation," Energies, MDPI, vol. 11(4), pages 1-15, March.
    2. Andoni, Merlinda & Robu, Valentin & Flynn, David & Abram, Simone & Geach, Dale & Jenkins, David & McCallum, Peter & Peacock, Andrew, 2019. "Blockchain technology in the energy sector: A systematic review of challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 143-174.
    3. Pearson, Simon & Wellnitz, Sonja & Crespo del Granado, Pedro & Hashemipour, Naser, 2022. "The value of TSO-DSO coordination in re-dispatch with flexible decentralized energy sources: Insights for Germany in 2030," Applied Energy, Elsevier, vol. 326(C).
    4. Abdullah M. Alabdullatif & Enrico H. Gerding & Alvaro Perez-Diaz, 2020. "Market Design and Trading Strategies for Community Energy Markets with Storage and Renewable Supply," Energies, MDPI, vol. 13(4), pages 1-31, February.
    5. Rae, Callum & Kerr, Sandy & Maroto-Valer, M. Mercedes, 2020. "Upscaling smart local energy systems: A review of technical barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    6. Binod Prasad Koirala & José Pablo Chaves Ávila & Tomás Gómez & Rudi A. Hakvoort & Paulien M. Herder, 2016. "Local Alternative for Energy Supply: Performance Assessment of Integrated Community Energy Systems," Energies, MDPI, vol. 9(12), pages 1-24, November.
    7. Karim L. Anaya & Michael G. Pollitt, 2021. "How to Procure Flexibility Services within the Electricity Distribution System: Lessons from an International Review of Innovation Projects," Energies, MDPI, vol. 14(15), pages 1-26, July.
    8. Rancilio, G. & Rossi, A. & Falabretti, D. & Galliani, A. & Merlo, M., 2022. "Ancillary services markets in europe: Evolution and regulatory trade-offs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    9. Cherrelle Eid & Rudi Hakvoort & Martin de Jong, 2016. "Global trends in the political economy of smart grids: A tailored perspective on 'smart' for grids in transition," WIDER Working Paper Series 022, World Institute for Development Economic Research (UNU-WIDER).
    10. Konstantinos Kotsalos & Ismael Miranda & Nuno Silva & Helder Leite, 2019. "A Horizon Optimization Control Framework for the Coordinated Operation of Multiple Distributed Energy Resources in Low Voltage Distribution Networks," Energies, MDPI, vol. 12(6), pages 1-27, March.
    11. Ajla Mehinovic & Matej Zajc & Nermin Suljanovic, 2023. "Interpretation and Quantification of the Flexibility Sources Location on the Flexibility Service in the Distribution Grid," Energies, MDPI, vol. 16(2), pages 1-18, January.
    12. Pol Olivella-Rosell & Pau Lloret-Gallego & Íngrid Munné-Collado & Roberto Villafafila-Robles & Andreas Sumper & Stig Ødegaard Ottessen & Jayaprakash Rajasekharan & Bernt A. Bremdal, 2018. "Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level," Energies, MDPI, vol. 11(4), pages 1-19, April.
    13. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    14. Joao C. Ferreira & Ana Lucia Martins, 2018. "Building a Community of Users for Open Market Energy," Energies, MDPI, vol. 11(9), pages 1-21, September.
    15. Liu, Hui & Huang, Kai & Wang, Ni & Qi, Junjian & Wu, Qiuwei & Ma, Shicong & Li, Canbing, 2019. "Optimal dispatch for participation of electric vehicles in frequency regulation based on area control error and area regulation requirement," Applied Energy, Elsevier, vol. 240(C), pages 46-55.
    16. Haas, Christian & Kempa, Karol & Moslener, Ulf, 2023. "Dealing with deep uncertainty in the energy transition: What we can learn from the electricity and transportation sectors," Energy Policy, Elsevier, vol. 179(C).
    17. Jianfei Shen & Fengyun Li & Di Shi & Hongze Li & Xinhua Yu, 2018. "Factors Affecting the Economics of Distributed Natural Gas-Combined Cooling, Heating and Power Systems in China: A Systematic Analysis Based on the Integrated Decision Making Trial and Evaluation Labo," Energies, MDPI, vol. 11(9), pages 1-28, September.
    18. Danica Djurić Ilić, 2020. "Classification of Measures for Dealing with District Heating Load Variations—A Systematic Review," Energies, MDPI, vol. 14(1), pages 1-27, December.
    19. Finck, Christian & Li, Rongling & Zeiler, Wim, 2020. "Optimal control of demand flexibility under real-time pricing for heating systems in buildings: A real-life demonstration," Applied Energy, Elsevier, vol. 263(C).
    20. Freitas Gomes, Icaro Silvestre & Perez, Yannick & Suomalainen, Emilia, 2020. "Coupling small batteries and PV generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(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:eee:appene:v:222:y:2018:i:c:p:993-1022. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.