IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v283y2021ics0306261920317311.html
   My bibliography  Save this article

Towards realization of an Energy Internet: Designing distributed energy systems using game-theoretic approach

Author

Listed:
  • Perera, A.T.D.
  • Wang, Z.
  • Nik, Vahid M.
  • Scartezzini, Jean-Louis

Abstract

Distributed energy systems play a significant role in the integration of renewable energy technologies. The Energy Internet links a fleet of distributed energy systems to each other and with the grid. Interactions between the distributed energy systems via information sharing could significantly enhance the efficiency of their real-time operation. However, privacy and security concerns hinder such interactions. A game-theoretic approach can help in this regard, and enable consideration of some of these factors when maintaining interactions between energy systems. Although a game-theoretic approach is used to understand energy systems' operation, such complex interactions between the energy systems are not considered at the early design phase, leading to many practical problems, and often leading to suboptimal designs. The present study introduces a game-theoretic approach that enables consideration of complex interactions among energy systems at the early design phase. Three different architectures are considered in the study, i.e., energy eystem prior to grid (ESPG), fully cooperative (FCS), and non-cooperative (NCS) scenarios, in which each distributed energy system is taken as an agent. A novel distributed optimization algorithm is developed for both FCS and NCS. The study reveals that FCS and NCS reduce the cost, respectively, by 30% and 15% compared to ESPG. In addition to cost reduction, there is a significant change in the energy system design when moving from FCS to NCS scenarios, clearly indicating the requirement for a scenario that lies between NCS and FCS. This will lead to reducing design costs while maintaining privacy.

Suggested Citation

  • Perera, A.T.D. & Wang, Z. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2021. "Towards realization of an Energy Internet: Designing distributed energy systems using game-theoretic approach," Applied Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920317311
    DOI: 10.1016/j.apenergy.2020.116349
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920317311
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2020.116349?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. Cai, Hanmin & You, Shi & Wu, Jianzhong, 2020. "Agent-based distributed demand response in district heating systems," Applied Energy, Elsevier, vol. 262(C).
    2. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid," Applied Energy, Elsevier, vol. 190(C), pages 232-248.
    3. Jing, Rui & Wang, Meng & Liang, Hao & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2018. "Multi-objective optimization of a neighborhood-level urban energy network: Considering Game-theory inspired multi-benefit allocation constraints," Applied Energy, Elsevier, vol. 231(C), pages 534-548.
    4. Sansavini, G. & Piccinelli, R. & Golea, L.R. & Zio, E., 2014. "A stochastic framework for uncertainty analysis in electric power transmission systems with wind generation," Renewable Energy, Elsevier, vol. 64(C), pages 71-81.
    5. Moazami, Amin & Nik, Vahid M. & Carlucci, Salvatore & Geving, Stig, 2019. "Impacts of future weather data typology on building energy performance – Investigating long-term patterns of climate change and extreme weather conditions," Applied Energy, Elsevier, vol. 238(C), pages 696-720.
    6. Wang, Zhengchao & Perera, A.T.D., 2020. "Integrated platform to design robust energy internet," Applied Energy, Elsevier, vol. 269(C).
    7. Perera, A.T.D. & Nik, Vahid M. & Wickramasinghe, P.U. & Scartezzini, Jean-Louis, 2019. "Redefining energy system flexibility for distributed energy system design," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    8. Christos-Spyridon Karavas & Konstantinos Arvanitis & George Papadakis, 2017. "A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids," Energies, MDPI, vol. 10(11), pages 1-22, November.
    9. Basir Khan, M. Reyasudin & Jidin, Razali & Pasupuleti, Jagadeesh & Shaaya, Sharifah Azwa, 2015. "Optimal combination of solar, wind, micro-hydro and diesel systems based on actual seasonal load profiles for a resort island in the South China Sea," Energy, Elsevier, vol. 82(C), pages 80-97.
    10. Motalleb, Mahdi & Siano, Pierluigi & Ghorbani, Reza, 2019. "Networked Stackelberg Competition in a Demand Response Market," Applied Energy, Elsevier, vol. 239(C), pages 680-691.
    11. A. T. D. Perera & Vahid M. Nik & Deliang Chen & Jean-Louis Scartezzini & Tianzhen Hong, 2020. "Quantifying the impacts of climate change and extreme climate events on energy systems," Nature Energy, Nature, vol. 5(2), pages 150-159, February.
    12. Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2016. "Energy Internet: The business perspective," Applied Energy, Elsevier, vol. 178(C), pages 212-222.
    13. Lund, H. & Mathiesen, B.V., 2009. "Energy system analysis of 100% renewable energy systems—The case of Denmark in years 2030 and 2050," Energy, Elsevier, vol. 34(5), pages 524-531.
    14. Ćosić, Boris & Krajačić, Goran & Duić, Neven, 2012. "A 100% renewable energy system in the year 2050: The case of Macedonia," Energy, Elsevier, vol. 48(1), pages 80-87.
    15. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "An integrated approach to design site specific distributed electrical hubs combining optimization, multi-criterion assessment and decision making," Energy, Elsevier, vol. 134(C), pages 103-120.
    16. Perera, A.T.D. & Coccolo, Silvia & Scartezzini, Jean-Louis & Mauree, Dasaraden, 2018. "Quantifying the impact of urban climate by extending the boundaries of urban energy system modeling," Applied Energy, Elsevier, vol. 222(C), pages 847-860.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fioriti, Davide & Frangioni, Antonio & Poli, Davide, 2021. "Optimal sizing of energy communities with fair revenue sharing and exit clauses: Value, role and business model of aggregators and users," Applied Energy, Elsevier, vol. 299(C).
    2. Perera, A.T.D. & Zhao, Bingyu & Wang, Zhe & Soga, Kenichi & Hong, Tianzhen, 2023. "Optimal design of microgrids to improve wildfire resilience for vulnerable communities at the wildland-urban interface," Applied Energy, Elsevier, vol. 335(C).
    3. Perera, A.T.D. & Khayatian, F. & Eggimann, S. & Orehounig, K. & Halgamuge, Saman, 2022. "Quantifying the climate and human-system-driven uncertainties in energy planning by using GANs," Applied Energy, Elsevier, vol. 328(C).
    4. Marta Biegańska, 2022. "IoT-Based Decentralized Energy Systems," Energies, MDPI, vol. 15(21), pages 1-20, October.
    5. Kiani-Moghaddam, Mohammad & Soltani, Mohsen N. & Kalogirou, Soteris A. & Mahian, Omid & Arabkoohsar, Ahmad, 2023. "A review of neighborhood level multi-carrier energy hubs—uncertainty and problem-solving process," Energy, Elsevier, vol. 281(C).

    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. Perera, A.T.D. & Hong, Tianzhen, 2023. "Vulnerability and resilience of urban energy ecosystems to extreme climate events: A systematic review and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    2. Perera, A.T.D. & Zhao, Bingyu & Wang, Zhe & Soga, Kenichi & Hong, Tianzhen, 2023. "Optimal design of microgrids to improve wildfire resilience for vulnerable communities at the wildland-urban interface," Applied Energy, Elsevier, vol. 335(C).
    3. Perera, A.T.D. & Javanroodi, Kavan & Nik, Vahid M., 2021. "Climate resilient interconnected infrastructure: Co-optimization of energy systems and urban morphology," Applied Energy, Elsevier, vol. 285(C).
    4. Wang, Zhengchao & Perera, A.T.D., 2020. "Integrated platform to design robust energy internet," Applied Energy, Elsevier, vol. 269(C).
    5. Perera, A.T.D. & Soga, Kenichi & Xu, Yujie & Nico, Peter S. & Hong, Tianzhen, 2023. "Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems," Applied Energy, Elsevier, vol. 340(C).
    6. Perera, A.T.D. & Kamalaruban, Parameswaran, 2021. "Applications of reinforcement learning in energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    7. Nik, Vahid M. & Moazami, Amin, 2021. "Using collective intelligence to enhance demand flexibility and climate resilience in urban areas," Applied Energy, Elsevier, vol. 281(C).
    8. Mauree, Dasaraden & Naboni, Emanuele & Coccolo, Silvia & Perera, A.T.D. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2019. "A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 733-746.
    9. Perera, A.T.D. & Nik, Vahid M. & Wickramasinghe, P.U. & Scartezzini, Jean-Louis, 2019. "Redefining energy system flexibility for distributed energy system design," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    10. Karni Siraganyan & Amarasinghage Tharindu Dasun Perera & Jean-Louis Scartezzini & Dasaraden Mauree, 2019. "Eco-Sim: A Parametric Tool to Evaluate the Environmental and Economic Feasibility of Decentralized Energy Systems," Energies, MDPI, vol. 12(5), pages 1-22, February.
    11. Perera, A.T.D. & Wickramasinghe, P.U. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2019. "Machine learning methods to assist energy system optimization," Applied Energy, Elsevier, vol. 243(C), pages 191-205.
    12. Perera, A.T.D. & Khayatian, F. & Eggimann, S. & Orehounig, K. & Halgamuge, Saman, 2022. "Quantifying the climate and human-system-driven uncertainties in energy planning by using GANs," Applied Energy, Elsevier, vol. 328(C).
    13. Ren, Fukang & Lin, Xiaozhen & Wei, Ziqing & Zhai, Xiaoqiang & Yang, Jianrong, 2022. "A novel planning method for design and dispatch of hybrid energy systems," Applied Energy, Elsevier, vol. 321(C).
    14. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid," Applied Energy, Elsevier, vol. 190(C), pages 232-248.
    15. Perera, A.T.D. & Coccolo, Silvia & Scartezzini, Jean-Louis & Mauree, Dasaraden, 2018. "Quantifying the impact of urban climate by extending the boundaries of urban energy system modeling," Applied Energy, Elsevier, vol. 222(C), pages 847-860.
    16. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    17. Lund, Henrik & Thellufsen, Jakob Zinck & Sorknæs, Peter & Mathiesen, Brian Vad & Chang, Miguel & Madsen, Poul Thøis & Kany, Mikkel Strunge & Skov, Iva Ridjan, 2022. "Smart energy Denmark. A consistent and detailed strategy for a fully decarbonized society," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    18. Cerovac, Tin & Ćosić, Boris & Pukšec, Tomislav & Duić, Neven, 2014. "Wind energy integration into future energy systems based on conventional plants – The case study of Croatia," Applied Energy, Elsevier, vol. 135(C), pages 643-655.
    19. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    20. Maruf, Md. Nasimul Islam, 2021. "Open model-based analysis of a 100% renewable and sector-coupled energy system–The case of Germany in 2050," Applied Energy, Elsevier, vol. 288(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:283:y:2021:i:c:s0306261920317311. 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.