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Infrastructure based on supernodes and software agents for the implementation of energy markets in demand-response programs


  • Lopez-Rodriguez, I.
  • Hernandez-Tejera, M.


The most successful peer-to-peer networks are based on the concept of supernode, which is an operating point of the network that provides services and advanced functionalities to other nodes. Inspired by this idea, this paper proposes to integrate nodes that provide intelligent advanced services in the future architecture of the electrical grid. Besides facilitating the access to data services such as demand estimations and weather forecasts, these nodes are especially meant to hold virtual environments in which software agents, after being contracted, negotiate on behalf of users in energy markets. This architecture is designed to be compatible with the Energy Interoperation OASIS standard. The capabilities and feasibility of the proposal is demonstrated through realistic experiments based on OpenADR programs, in which users exchange energy by using parallel auction markets. In addition, in order to have the roles of buyer and seller in demand-response programs, thus allowing the creation of markets, a conceptual model based on negative loads and critical loads is provided. The experiments have proven that the proposed architecture facilitates the implementation of advanced distributed management systems in order that smart metering infrastructures, in contrast with traditional agent-based solutions, are released to perform negotiation tasks and access data services, while users gain both autonomy and decision-making capacity.

Suggested Citation

  • Lopez-Rodriguez, I. & Hernandez-Tejera, M., 2015. "Infrastructure based on supernodes and software agents for the implementation of energy markets in demand-response programs," Applied Energy, Elsevier, vol. 158(C), pages 1-11.
  • Handle: RePEc:eee:appene:v:158:y:2015:i:c:p:1-11
    DOI: 10.1016/j.apenergy.2015.08.039

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    References listed on IDEAS

    1. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    2. Li, Gong & Shi, Jing, 2012. "Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions," Applied Energy, Elsevier, vol. 99(C), pages 13-22.
    3. Tim Hoppe, 2008. "An Experimental Analysis of Parallel Multiple Auctions," FEMM Working Papers 08031, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    4. Shen, Bo & Ghatikar, Girish & Lei, Zeng & Li, Jinkai & Wikler, Greg & Martin, Phil, 2014. "The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges," Applied Energy, Elsevier, vol. 130(C), pages 814-823.
    5. Zhao, Bo & Xue, Meidong & Zhang, Xuesong & Wang, Caisheng & Zhao, Junhui, 2015. "An MAS based energy management system for a stand-alone microgrid at high altitude," Applied Energy, Elsevier, vol. 143(C), pages 251-261.
    6. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico, 2014. "An integrated framework of agent-based modelling and robust optimization for microgrid energy management," Applied Energy, Elsevier, vol. 129(C), pages 70-88.
    7. Kyriakarakos, George & Piromalis, Dimitrios D. & Dounis, Anastasios I. & Arvanitis, Konstantinos G. & Papadakis, George, 2013. "Intelligent demand side energy management system for autonomous polygeneration microgrids," Applied Energy, Elsevier, vol. 103(C), pages 39-51.
    8. Wang, Zhu & Wang, Lingfeng & Dounis, Anastasios I. & Yang, Rui, 2012. "Multi-agent control system with information fusion based comfort model for smart buildings," Applied Energy, Elsevier, vol. 99(C), pages 247-254.
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    3. Skarvelis-Kazakos, Spyros & Papadopoulos, Panagiotis & Grau Unda, Iñaki & Gorman, Terry & Belaidi, Abdelhafid & Zigan, Stefan, 2016. "Multiple energy carrier optimisation with intelligent agents," Applied Energy, Elsevier, vol. 167(C), pages 323-335.

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