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A high-temperature heat pump for compressed heat energy storage applications: Design, modeling, and performance: Design, modeling, and performance

  • Abdelrahman H. Hassan
  • , José M. Corberán
  • , Miguel Ramirez
  • , Felipe Trebilcock-Kelly
  • , Jorge Payá
  • Polytechnic University of Valencia
  • Zagazig University

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

40 Citas (Scopus)
1 Descargas (Pure)

Resumen

The current paper presents the design and performance of a high-temperature heat pump (HTHP) integrated in an innovative, sensible, and latent heat storage system. The HTHP has been designed to work between a heat source from 40 to 100 °C and a heat sink above 130 °C. An initial refrigerant analysis has revealed that R-1233zd(E) is the best candidate to meet the required performance and environmental considerations. The first part of this paper deals with the sizing and selection of the main components while discussing the challenges and working limits. A numerical model is also presented and validated. The second part of the paper is dedicated to develop parametric studies and performance maps under different operating conditions. The results show that the current HTHP, at a source temperature of 80 °C, consumes from 3.23 to 9.88 kW by varying the compressor’s speed from 500 to 1500 rpm. Heat production is achieved in the form of latent heat (7.40 to 21.59 kW) and sensible heat (from 6.35 to 17.94 kW). The heating coefficient of performance (COPHTHP) is around 4.
Idioma originalInglés
Páginas (desde-hasta)10833-10848
Número de páginas16
PublicaciónEnergy Reports
Volumen8
DOI
EstadoPublicada - nov 2022

Palabras clave

  • Pumped thermal energy storage
  • High-temperature heat pump
  • Modeling
  • Subcooling
  • Superheat
  • Refrigerants

Project and Funding Information

  • Project ID
  • info:eu-repo/grantAgreement/EC/H2020/764042/EU/Compressed Heat Energy Storage for Energy from Renewable sources/CHESTER
  • Funding Info
  • This work has been partially funded by grant agreement No. 764042 (CHESTER project) of the European Union’s Horizon 2020 research and innovation program. The authors would like to express their deep gratitude to Prof. Dr. Jose Miguel Corberán Salvador for his perseverance, encouragement, and invaluable guidance during this work.

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