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A real-time demand response algorithm for heterogeneous devices in buildings and homes

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  • Hong, Seung Ho
  • Yu, Mengmeng
  • Huang, Xuefei

Abstract

The growing demand for electricity, coupled with increased efficiency requirements, creates new opportunities for the development of demand-side management systems. Here we describe an approach for load allocation among different classes of device. We adopt the concept of strategic choice to determine the optimal strategy for a given situation. Electricity resources are allocated based on demand, priority, fairness, the available electrical resources, and the budget, so that even when the unit price is high (i.e., the available resources are restricted), higher-priority devices continue to operate without interruption. When the price falls, resources are distributed to satisfy the requirements of a larger number of devices. We include ESSs (energy storage systems) in the algorithm to reserve energy during low-price times for use during high-price times. The algorithm described here can be used to allocate resources among heterogeneous devices, and has potential not only to reduce peak demand but also to increase the overall efficiency of the system.

Suggested Citation

  • Hong, Seung Ho & Yu, Mengmeng & Huang, Xuefei, 2015. "A real-time demand response algorithm for heterogeneous devices in buildings and homes," Energy, Elsevier, vol. 80(C), pages 123-132.
  • Handle: RePEc:eee:energy:v:80:y:2015:i:c:p:123-132
    DOI: 10.1016/j.energy.2014.11.053
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    1. Arghira, Nicoleta & Hawarah, Lamis & Ploix, Stéphane & Jacomino, Mireille, 2012. "Prediction of appliances energy use in smart homes," Energy, Elsevier, vol. 48(1), pages 128-134.
    2. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    3. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    4. Blumsack, Seth & Fernandez, Alisha, 2012. "Ready or not, here comes the smart grid!," Energy, Elsevier, vol. 37(1), pages 61-68.
    5. Li, Xiao Hui & Hong, Seung Ho, 2014. "User-expected price-based demand response algorithm for a home-to-grid system," Energy, Elsevier, vol. 64(C), pages 437-449.
    6. Doostizadeh, Meysam & Ghasemi, Hassan, 2012. "A day-ahead electricity pricing model based on smart metering and demand-side management," Energy, Elsevier, vol. 46(1), pages 221-230.
    7. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2014. "Scheduling policies for two-state smart-home appliances in dynamic electricity pricing environments," Energy, Elsevier, vol. 69(C), pages 455-469.
    8. Soares, Ana & Antunes, Carlos Henggeler & Oliveira, Carlos & Gomes, Álvaro, 2014. "A multi-objective genetic approach to domestic load scheduling in an energy management system," Energy, Elsevier, vol. 77(C), pages 144-152.
    9. Lund, Henrik & Andersen, Anders N. & Østergaard, Poul Alberg & Mathiesen, Brian Vad & Connolly, David, 2012. "From electricity smart grids to smart energy systems – A market operation based approach and understanding," Energy, Elsevier, vol. 42(1), pages 96-102.
    10. Yousefi, Shaghayegh & Moghaddam, Mohsen Parsa & Majd, Vahid Johari, 2011. "Optimal real time pricing in an agent-based retail market using a comprehensive demand response model," Energy, Elsevier, vol. 36(9), pages 5716-5727.
    11. Hong, Seung Ho & Kim, Se Hwan & Kim, Gi Myung & Kim, Hyung Lae, 2014. "Experimental evaluation of BZ-GW (BACnet-ZigBee smart grid gateway) for demand response in buildings," Energy, Elsevier, vol. 65(C), pages 62-70.
    12. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    13. Cappers, Peter & Goldman, Charles & Kathan, David, 2010. "Demand response in U.S. electricity markets: Empirical evidence," Energy, Elsevier, vol. 35(4), pages 1526-1535.
    14. Greening, Lorna A., 2010. "Demand response resources: Who is responsible for implementation in a deregulated market?," Energy, Elsevier, vol. 35(4), pages 1518-1525.
    15. Faria, P. & Vale, Z., 2011. "Demand response in electrical energy supply: An optimal real time pricing approach," Energy, Elsevier, vol. 36(8), pages 5374-5384.
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