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Influence of the heat storage size on the plant performance in a Smart User case study

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  • Chesi, Andrea
  • Ferrara, Giovanni
  • Ferrari, Lorenzo
  • Magnani, Sandro
  • Tarani, Fabio

Abstract

The increasing diffusion of renewable energy sources are posing new challenges to the power grid due to their intrinsic unpredictability causing poor power quality, line congestion and unreliable and unsecure grid operations. In the future, power grid operators may require to the customers/producers a prescribed exchange profile, leading to a diffusion of storage systems or prime movers (especially small combined heat and power for distributed resources) able to balance renewable sources fluctuations. In this latter case, one of the major issue is the efficient use of the heat co-generated: the adoption of thermal storages appears to be necessary. In this paper, the energy performance of a Smart User, i.e. a dwelling with renewable energy sources, a combined cooling, heat, and power system, and heat and cooling back-up generators, is estimated by means of a purposely developed TRNSYS unsteady model. A virtual stand-alone operating condition is imposed for the analysed building as an arbitrary profile of power exchange with the grid. The balancing of renewable sources fluctuations imposes a non-negligible part of the heat from the prime mover to be wasted and a sensible consumption for auxiliary devices (i.e. the auxiliary boiler and the compression chiller). By applying a thermal storage, and increasing its capacity, the fraction of heat wasted and the supply from other devices is remarkably changed, showing different plant performance and efficiencies. The Smart User primary energy consumptions of the different configurations are compared to several options, showing appreciable differences in the performance.

Suggested Citation

  • Chesi, Andrea & Ferrara, Giovanni & Ferrari, Lorenzo & Magnani, Sandro & Tarani, Fabio, 2013. "Influence of the heat storage size on the plant performance in a Smart User case study," Applied Energy, Elsevier, vol. 112(C), pages 1454-1465.
  • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:1454-1465
    DOI: 10.1016/j.apenergy.2013.01.089
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    Cited by:

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    6. Mongibello, Luigi & Bianco, Nicola & Caliano, Martina & Graditi, Giorgio, 2016. "Comparison between two different operation strategies for a heat-driven residential natural gas-fired CHP system: Heat dumping vs. load partialization," Applied Energy, Elsevier, vol. 184(C), pages 55-67.
    7. 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.
    8. Ferrari, Lorenzo & Esposito, Fabio & Becciani, Michele & Ferrara, Giovanni & Magnani, Sandro & Andreini, Mirko & Bellissima, Alessandro & Cantù, Matteo & Petretto, Giacomo & Pentolini, Massimo, 2017. "Development of an optimization algorithm for the energy management of an industrial Smart User," Applied Energy, Elsevier, vol. 208(C), pages 1468-1486.
    9. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    10. Adam, Alexandros & Fraga, Eric S. & Brett, Dan J.L., 2015. "Options for residential building services design using fuel cell based micro-CHP and the potential for heat integration," Applied Energy, Elsevier, vol. 138(C), pages 685-694.
    11. Kocijel, Lino & Mrzljak, Vedran & Glažar, Vladimir, 2020. "Numerical analysis of geometrical and process parameters influence on temperature stratification in a large volumetric heat storage tank," Energy, Elsevier, vol. 194(C).
    12. Li, Gang & Zheng, Xuefei, 2016. "Thermal energy storage system integration forms for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 736-757.
    13. Liu, X.P. & Niu, J.L., 2014. "An optimal design analysis method for heat recovery devices in building applications," Applied Energy, Elsevier, vol. 129(C), pages 364-372.
    14. Stojiljković, Mirko M. & Ignjatović, Marko G. & Vučković, Goran D., 2015. "Greenhouse gases emission assessment in residential sector through buildings simulations and operation optimization," Energy, Elsevier, vol. 92(P3), pages 420-434.
    15. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
    16. Comodi, Gabriele & Giantomassi, Andrea & Severini, Marco & Squartini, Stefano & Ferracuti, Francesco & Fonti, Alessandro & Nardi Cesarini, Davide & Morodo, Matteo & Polonara, Fabio, 2015. "Multi-apartment residential microgrid with electrical and thermal storage devices: Experimental analysis and simulation of energy management strategies," Applied Energy, Elsevier, vol. 137(C), pages 854-866.
    17. Marguerite, C. & Andresen, G.B. & Dahl, M., 2018. "Multi-criteria analysis of storages integration and operation solutions into the district heating network of Aarhus – A simulation case study," Energy, Elsevier, vol. 158(C), pages 81-88.
    18. Guillermo Rey & Carlos Ulloa & Jose Luis Míguez & Elena Arce, 2016. "Development of an ICE-Based Micro-CHP System Based on a Stirling Engine; Methodology for a Comparative Study of its Performance and Sensitivity Analysis in Recreational Sailing Boats in Different Euro," Energies, MDPI, vol. 9(4), pages 1-14, March.
    19. Fang, Tingting & Lahdelma, Risto, 2016. "Optimization of combined heat and power production with heat storage based on sliding time window method," Applied Energy, Elsevier, vol. 162(C), pages 723-732.

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