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Comparison of Direct and Indirect Active Thermal Energy Storage Strategies for Large-Scale Solar Heating Systems

Author

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  • Xiaofeng Guo

    (ESIEE Paris, University of Paris Est, F-93162 Noisy le Grand, France
    LIED-PIERI, UMR 8236, CNRS, University of Paris Diderot (Paris 7), F-75013 Paris, France)

  • Alain Pascal Goumba

    (ESIEE Paris, University of Paris Est, F-93162 Noisy le Grand, France
    EFFICACITY, 14-20 boulevard Newton, F-77447 Marne la Vallée CEDEX 2, France)

  • Cheng Wang

    (Jiangsu Provincial Key Laboratory of Oil & Gas Storage and Transportation Technology, Changzhou University, Changzhou, Jiangsu 213016, China)

Abstract

Large-scale solar heating for the building sector requires an adequate Thermal Energy Storage (TES) strategy. TES plays the role of load shifting between the energy demand and the solar irradiance and thus makes the annual production optimal. In this study, we report a simplified algorithm uniquely based on energy flux, to evaluate the role of active TES on the annual performance of a large-scale solar heating for residential thermal energy supply. The program considers different types of TES, i.e., direct and indirect, as well as their specifications in terms of capacity, storage density, charging/discharging limits, etc. Our result confirms the auto-regulation ability of indirect (latent using Phase Change Material (PCM), or Borehole thermal storage (BTES) in soil) TES which makes the annual performance comparable to that of direct (sensible with hot water) TES. The charging and discharging restrictions of the latent TES, until now considered as a weak point, could retard the achievement of fully-charged situation and prolong the charging process. With its compact volume, the indirect TES turns to be promising for large-scale solar thermal application.

Suggested Citation

  • Xiaofeng Guo & Alain Pascal Goumba & Cheng Wang, 2019. "Comparison of Direct and Indirect Active Thermal Energy Storage Strategies for Large-Scale Solar Heating Systems," Energies, MDPI, vol. 12(10), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:10:p:1948-:d:233115
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    References listed on IDEAS

    as
    1. Reilly, Aidan & Kinnane, Oliver, 2017. "The impact of thermal mass on building energy consumption," Applied Energy, Elsevier, vol. 198(C), pages 108-121.
    2. Wang, Weilong & Guo, Shaopeng & Li, Hailong & Yan, Jinyue & Zhao, Jun & Li, Xun & Ding, Jing, 2014. "Experimental study on the direct/indirect contact energy storage container in mobilized thermal energy system (M-TES)," Applied Energy, Elsevier, vol. 119(C), pages 181-189.
    3. Castell, A. & Belusko, M. & Bruno, F. & Cabeza, L.F., 2011. "Maximisation of heat transfer in a coil in tank PCM cold storage system," Applied Energy, Elsevier, vol. 88(11), pages 4120-4127.
    4. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    5. Guo, Shaopeng & Li, Hailong & Zhao, Jun & Li, Xun & Yan, Jinyue, 2013. "Numerical simulation study on optimizing charging process of the direct contact mobilized thermal energy storage," Applied Energy, Elsevier, vol. 112(C), pages 1416-1423.
    6. Powell, Kody M. & Kim, Jong Suk & Cole, Wesley J. & Kapoor, Kriti & Mojica, Jose L. & Hedengren, John D. & Edgar, Thomas F., 2016. "Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market," Energy, Elsevier, vol. 113(C), pages 52-63.
    7. Gadd, Henrik & Werner, Sven, 2014. "Achieving low return temperatures from district heating substations," Applied Energy, Elsevier, vol. 136(C), pages 59-67.
    8. Wang, Sixian & Zhang, Xuelin & Yang, Luwei & Zhou, Yuan & Wang, Junjie, 2016. "Experimental study of compressed air energy storage system with thermal energy storage," Energy, Elsevier, vol. 103(C), pages 182-191.
    9. Guo, Xiaofeng & Goumba, Alain Pascal, 2018. "Air source heat pump for domestic hot water supply: Performance comparison between individual and building scale installations," Energy, Elsevier, vol. 164(C), pages 794-802.
    10. Guo, Xiaofeng & Hendel, Martin, 2018. "Urban water networks as an alternative source for district heating and emergency heat-wave cooling," Energy, Elsevier, vol. 145(C), pages 79-87.
    11. Merlin, Kevin & Delaunay, Didier & Soto, Jérôme & Traonvouez, Luc, 2016. "Heat transfer enhancement in latent heat thermal storage systems: Comparative study of different solutions and thermal contact investigation between the exchanger and the PCM," Applied Energy, Elsevier, vol. 166(C), pages 107-116.
    12. Ayón, X. & Gruber, J.K. & Hayes, B.P. & Usaola, J. & Prodanović, M., 2017. "An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands," Applied Energy, Elsevier, vol. 198(C), pages 1-11.
    13. Rezaie, Behnaz & Rosen, Marc A., 2012. "District heating and cooling: Review of technology and potential enhancements," Applied Energy, Elsevier, vol. 93(C), pages 2-10.
    14. Seck, Gondia Sokhna & Guerassimoff, Gilles & Maïzi, Nadia, 2015. "Heat recovery using heat pumps in non-energy intensive industry: Are Energy Saving Certificates a solution for the food and drink industry in France?," Applied Energy, Elsevier, vol. 156(C), pages 374-389.
    15. Ioan Sarbu & Calin Sebarchievici, 2018. "A Comprehensive Review of Thermal Energy Storage," Sustainability, MDPI, vol. 10(1), pages 1-32, January.
    16. Gadd, Henrik & Werner, Sven, 2013. "Heat load patterns in district heating substations," Applied Energy, Elsevier, vol. 108(C), pages 176-183.
    17. Lund, Henrik & Werner, Sven & Wiltshire, Robin & Svendsen, Svend & Thorsen, Jan Eric & Hvelplund, Frede & Mathiesen, Brian Vad, 2014. "4th Generation District Heating (4GDH)," Energy, Elsevier, vol. 68(C), pages 1-11.
    18. Verda, Vittorio & Colella, Francesco, 2011. "Primary energy savings through thermal storage in district heating networks," Energy, Elsevier, vol. 36(7), pages 4278-4286.
    19. Wang, Cheng & Guo, Xiaofeng & Zhu, Ye, 2019. "Energy saving with Optic-Variable Wall for stable air temperature control," Energy, Elsevier, vol. 173(C), pages 38-47.
    20. Parra, David & Norman, Stuart A. & Walker, Gavin S. & Gillott, Mark, 2017. "Optimum community energy storage for renewable energy and demand load management," Applied Energy, Elsevier, vol. 200(C), pages 358-369.
    21. Fumey, B. & Weber, R. & Baldini, L., 2017. "Liquid sorption heat storage – A proof of concept based on lab measurements with a novel spiral fined heat and mass exchanger design," Applied Energy, Elsevier, vol. 200(C), pages 215-225.
    22. Yang, Jialin & Yang, Lijun & Xu, Chao & Du, Xiaoze, 2016. "Experimental study on enhancement of thermal energy storage with phase-change material," Applied Energy, Elsevier, vol. 169(C), pages 164-176.
    23. Kensby, Johan & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Potential of residential buildings as thermal energy storage in district heating systems – Results from a pilot test," Applied Energy, Elsevier, vol. 137(C), pages 773-781.
    24. Brueckner, Sarah & Miró, Laia & Cabeza, Luisa F. & Pehnt, Martin & Laevemann, Eberhard, 2014. "Methods to estimate the industrial waste heat potential of regions – A categorization and literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 164-171.
    25. Kevin Ellingwood & Seyed Mostafa Safdarnejad & Khalid Rashid & Kody Powell, 2018. "Leveraging Energy Storage in a Solar-Tower and Combined Cycle Hybrid Power Plant," Energies, MDPI, vol. 12(1), pages 1-23, December.
    26. Buoro, Dario & Pinamonti, Piero & Reini, Mauro, 2014. "Optimization of a Distributed Cogeneration System with solar district heating," Applied Energy, Elsevier, vol. 124(C), pages 298-308.
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    Cited by:

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    2. Doračić, Borna & Pukšec, Tomislav & Schneider, Daniel Rolph & Duić, Neven, 2020. "The effect of different parameters of the excess heat source on the levelized cost of excess heat," Energy, Elsevier, vol. 201(C).
    3. Xue, Puning & Jiang, Yi & Zhou, Zhigang & Chen, Xin & Fang, Xiumu & Liu, Jing, 2019. "Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms," Energy, Elsevier, vol. 188(C).
    4. Danica Djurić Ilić, 2020. "Classification of Measures for Dealing with District Heating Load Variations—A Systematic Review," Energies, MDPI, vol. 14(1), pages 1-27, December.
    5. Zhao, Yin & Gong, Mingju & Sun, Jiawang & Han, Cuitian & Jing, Lei & Li, Bo & Zhao, Zhixuan, 2023. "A new hybrid optimization prediction strategy based on SH-Informer for district heating system," Energy, Elsevier, vol. 282(C).
    6. Antonio Rosato & Antonio Ciervo & Giovanni Ciampi & Michelangelo Scorpio & Sergio Sibilio, 2020. "Integration of Micro-Cogeneration Units and Electric Storages into a Micro-Scale Residential Solar District Heating System Operating with a Seasonal Thermal Storage," Energies, MDPI, vol. 13(20), pages 1-40, October.
    7. Behzadi, Amirmohammad & Holmberg, Sture & Duwig, Christophe & Haghighat, Fariborz & Ooka, Ryozo & Sadrizadeh, Sasan, 2022. "Smart design and control of thermal energy storage in low-temperature heating and high-temperature cooling systems: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).

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