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Modeling the impact of integrating solar thermal systems and heat pumps for domestic hot water in electric systems – The case study of Corvo Island

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  • Neves, Diana
  • Silva, Carlos A.

Abstract

The use of solar thermal systems with electricity backup and heat pumps as hot water suppliers in residential buildings seems to be a very promising way to increase energy efficiency. Nevertheless, the massive adoption of such solutions in small networks (neighborhood, village) may induce problems in the electric grid management. This study explores the impact of such systems in small electric grids, using an hourly electricity backup load model. To test and validate the model, we used the island of Corvo (Azores), a small isolated community where it is being implemented a project of electrification of domestic hot water systems (DHW). We consider different load scenarios to manage the backup of DHW systems and analyze its consequences on the peak load and overall energy demand. For Corvo, for the best case where the backup is limited and distributed along off-peak hours, we observed an increase of 24% in the peak load and 7.5% in the annual energy demand. Critical values of peak load are found in winter, when daily solar irradiation is lower than 2000 Wh/m2/day. We conclude that the solar thermal systems are responsible for most of the peak load increase, but since they have the flexibility to adjust the electric backup hours due to the thermal storage capacity, the use of these systems can minimize the impact on the grid. Heat pumps on the other hand, albeit being more efficient in terms electric backup, are less flexible to contribute to the grid management as they operate continuously.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:72:y:2014:i:c:p:113-124
    DOI: 10.1016/j.renene.2014.06.046
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    References listed on IDEAS

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    1. Hrastnik, Branimir & Franković, Bernard, 2001. "Solar energy demonstration zones in the Dalmatian region," Renewable Energy, Elsevier, vol. 24(3), pages 501-515.
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    Cited by:

    1. Zempila, Melina-Maria & Giannaros, Theodore M. & Bais, Alkiviadis & Melas, Dimitris & Kazantzidis, Andreas, 2016. "Evaluation of WRF shortwave radiation parameterizations in predicting Global Horizontal Irradiance in Greece," Renewable Energy, Elsevier, vol. 86(C), pages 831-840.
    2. Ana I.P. Salvador & Catarina P. Mouraz & Lídia Catarino & Victor Mestre & José Mendes Silva, 2021. "Housing Buildings’ Characterization at Corvo Village (Azores) Historical Center: Towards a Sustainable Rehabilitation Process," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    3. Mohanraj, M. & Belyayev, Ye. & Jayaraj, S. & Kaltayev, A., 2018. "Research and developments on solar assisted compression heat pump systems – A comprehensive review (Part-B: Applications)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 124-155.
    4. Graça Gomes, J. & Xu, H.J. & Yang, Q. & Zhao, C.Y., 2021. "An optimization study on a typical renewable microgrid energy system with energy storage," Energy, Elsevier, vol. 234(C).
    5. Meireles, I. & Sousa, V. & Bleys, B. & Poncelet, B., 2022. "Domestic hot water consumption pattern: Relation with total water consumption and air temperature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    6. 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.
    7. Karol Bot & Inoussa Laouali & António Ruano & Maria da Graça Ruano, 2021. "Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques," Energies, MDPI, vol. 14(18), pages 1-27, September.
    8. Neves, Diana & Pina, André & Silva, Carlos A., 2015. "Demand response modeling: A comparison between tools," Applied Energy, Elsevier, vol. 146(C), pages 288-297.
    9. Guzzi, Francesco & Neves, Diana & Silva, Carlos A., 2017. "Integration of smart grid mechanisms on microgrids energy modelling," Energy, Elsevier, vol. 129(C), pages 321-330.
    10. Groppi, Daniele & Pfeifer, Antun & Garcia, Davide Astiaso & Krajačić, Goran & Duić, Neven, 2021. "A review on energy storage and demand side management solutions in smart energy islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    11. Rehman, Hassam ur & Hirvonen, Janne & Sirén, Kai, 2017. "A long-term performance analysis of three different configurations for community-sized solar heating systems in high latitudes," Renewable Energy, Elsevier, vol. 113(C), pages 479-493.
    12. 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.
    13. Meschede, Henning, 2020. "Analysis on the demand response potential in hotels with varying probabilistic influencing time-series for the Canary Islands," Renewable Energy, Elsevier, vol. 160(C), pages 1480-1491.
    14. Ricardo A. Marques Lameirinhas & João Paulo N. Torres & João P. de Melo Cunha, 2022. "A Photovoltaic Technology Review: History, Fundamentals and Applications," Energies, MDPI, vol. 15(5), pages 1-44, March.
    15. 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.
    16. Magda I. El-Afifi & Magdi M. Saadawi & Abdelfattah A. Eladl, 2022. "Cogeneration Systems Performance Analysis as a Sustainable Clean Energy and Water Source Based on Energy Hubs Using the Archimedes Optimization Algorithm," Sustainability, MDPI, vol. 14(22), pages 1-26, November.

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