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Power demand control scenarios for smart grid applications with finite number of appliances

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  • Vardakas, John S.
  • Zorba, Nizar
  • Verikoukis, Christos V.

Abstract

In this paper we propose novel and more realistic analytical models for the determination of the peak demand under four power demand control scenarios. Each scenario considers a finite number of appliances installed in a residential area, with diverse power demands and different arrival rates of power requests. We develop recursive formulas for the efficient calculation of the peak demand under each scenario, which take into account the finite population of the appliances. Moreover, we associate each scenario with a proper real-time pricing process in order to derive the social welfare. The proposed analysis is validated through simulations. Moreover, the performance evaluation of the proposed formulas reveals that the absence of the assumption of finite number of appliances could lead to serious peak-demand over-estimations.

Suggested Citation

  • Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2016. "Power demand control scenarios for smart grid applications with finite number of appliances," Applied Energy, Elsevier, vol. 162(C), pages 83-98.
  • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:83-98
    DOI: 10.1016/j.apenergy.2015.10.008
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    References listed on IDEAS

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    1. Valenzuela, Jorge & Thimmapuram, Prakash R. & Kim, Jinho, 2012. "Modeling and simulation of consumer response to dynamic pricing with enabled technologies," Applied Energy, Elsevier, vol. 96(C), pages 122-132.
    2. Venkatesan, Naveen & Solanki, Jignesh & Solanki, Sarika Khushalani, 2012. "Residential Demand Response model and impact on voltage profile and losses of an electric distribution network," Applied Energy, Elsevier, vol. 96(C), pages 84-91.
    3. Di Giorgio, Alessandro & Liberati, Francesco, 2014. "Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models," Applied Energy, Elsevier, vol. 128(C), pages 119-132.
    4. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    5. Wissner, Matthias, 2011. "The Smart Grid - A saucerful of secrets?," Applied Energy, Elsevier, vol. 88(7), pages 2509-2518, July.
    6. Xue, Xue & Wang, Shengwei & Yan, Chengchu & Cui, Borui, 2015. "A fast chiller power demand response control strategy for buildings connected to smart grid," Applied Energy, Elsevier, vol. 137(C), pages 77-87.
    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. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2015. "Performance evaluation of power demand scheduling scenarios in a smart grid environment," Applied Energy, Elsevier, vol. 142(C), pages 164-178.
    9. 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.
    10. Su, Wencong & Chow, Mo-Yuen, 2012. "Computational intelligence-based energy management for a large-scale PHEV/PEV enabled municipal parking deck," Applied Energy, Elsevier, vol. 96(C), pages 171-182.
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