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Assessment of the potential use of demand response in DHW systems on isolated microgrids

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  • Neves, Diana
  • Pina, André
  • Silva, Carlos A.

Abstract

This work assesses the potential of demand response on isolated hybrid renewable energy systems, in order to optimize the systems' dispatch by minimizing the operation costs and the peak demand. The developed methodology models the implementation of solar thermal systems to replace non-renewable systems for the domestic hot water supply, and a demand response strategy to manage the electric backup required from the grid, in days of low solar radiation. The implementation of this system is compared between 10 isolated islands with different scales and energy systems in order to identify the potential energy savings introduced by solar thermal systems with demand response capabilities under different conditions.

Suggested Citation

  • Neves, Diana & Pina, André & Silva, Carlos A., 2018. "Assessment of the potential use of demand response in DHW systems on isolated microgrids," Renewable Energy, Elsevier, vol. 115(C), pages 989-998.
    • Handle: RePEc:eee:renene:v:115:y:2018:i:c:p:989-998
    DOI: 10.1016/j.renene.2017.09.027
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    References listed on IDEAS

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    1. Neves, Diana & Silva, Carlos A. & Connors, Stephen, 2014. "Design and implementation of hybrid renewable energy systems on micro-communities: A review on case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 935-946.
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    4. Neves, Diana & Silva, Carlos A., 2015. "Optimal electricity dispatch on isolated mini-grids using a demand response strategy for thermal storage backup with genetic algorithms," Energy, Elsevier, vol. 82(C), pages 436-445.
    5. Liu, Yanchao & Holzer, Jesse T. & Ferris, Michael C., 2015. "Extending the bidding format to promote demand response," Energy Policy, Elsevier, vol. 86(C), pages 82-92.
    6. Pina, André & Silva, Carlos & Ferrão, Paulo, 2012. "The impact of demand side management strategies in the penetration of renewable electricity," Energy, Elsevier, vol. 41(1), pages 128-137.
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    8. Cavallaro, Fausto & Ciraolo, Luigi, 2005. "A multicriteria approach to evaluate wind energy plants on an Italian island," Energy Policy, Elsevier, vol. 33(2), pages 235-244, January.
    9. Neves, Diana & Pina, André & Silva, Carlos A., 2015. "Demand response modeling: A comparison between tools," Applied Energy, Elsevier, vol. 146(C), pages 288-297.
    10. Ruddell, Benjamin L. & Salamanca, Francisco & Mahalov, Alex, 2014. "Reducing a semiarid city’s peak electrical demand using distributed cold thermal energy storage," Applied Energy, Elsevier, vol. 134(C), pages 35-44.
    11. Jang, Dongsik & Eom, Jiyong & Jae Park, Min & Jeung Rho, Jae, 2016. "Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers," Energy Policy, Elsevier, vol. 88(C), pages 11-26.
    12. Andaloro, Antonio Pietro Francesco & Salomone, Roberta & Andaloro, Laura & Briguglio, Nicola & Sparacia, Sergio, 2012. "Alternative energy scenarios for small islands: A case study from Salina Island (Aeolian Islands, Southern Italy)," Renewable Energy, Elsevier, vol. 47(C), pages 135-146.
    13. Neves, Diana & Brito, Miguel C. & Silva, Carlos A., 2016. "Impact of solar and wind forecast uncertainties on demand response of isolated microgrids," Renewable Energy, Elsevier, vol. 87(P2), pages 1003-1015.
    14. Dyson, Mark E.H. & Borgeson, Samuel D. & Tabone, Michaelangelo D. & Callaway, Duncan S., 2014. "Using smart meter data to estimate demand response potential, with application to solar energy integration," Energy Policy, Elsevier, vol. 73(C), pages 607-619.
    15. Neves, Diana & Silva, Carlos A., 2014. "Modeling the impact of integrating solar thermal systems and heat pumps for domestic hot water in electric systems – The case study of Corvo Island," Renewable Energy, Elsevier, vol. 72(C), pages 113-124.
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    8. Xu, Qingyang & Sun, Feihu & Cai, Qiran & Liu, Li-Jing & Zhang, Kun & Liang, Qiao-Mei, 2022. "Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China," Renewable Energy, Elsevier, vol. 190(C), pages 945-958.

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