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Energy and comfort: A new type for TRNSYS

Author

Listed:
  • Solaini, G.
  • Rossi, G.
  • Dall'O', G.
  • Drago, P.

Abstract

Two subroutines have been developed which permit users of the TRNSYS programme to calculate the parameters of ambiental comfort (PMV and PPD).

Suggested Citation

  • Solaini, G. & Rossi, G. & Dall'O', G. & Drago, P., 1996. "Energy and comfort: A new type for TRNSYS," Renewable Energy, Elsevier, vol. 8(1), pages 56-60.
    • Handle: RePEc:eee:renene:v:8:y:1996:i:1:p:56-60
    DOI: 10.1016/0960-1481(96)88820-3
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    Citations

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    Cited by:

    1. Domenico Palladino & Iole Nardi & Cinzia Buratti, 2020. "Artificial Neural Network for the Thermal Comfort Index Prediction: Development of a New Simplified Algorithm," Energies, MDPI, vol. 13(17), pages 1-27, September.
    2. Jarvinen, J. & Goldsworthy, M. & White, S. & Pudney, P. & Belusko, M. & Bruno, F., 2021. "Evaluating the utility of passive thermal storage as an energy storage system on the Australian energy market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    3. Shrivastava, R.L. & Vinod Kumar, & Untawale, S.P., 2017. "Modeling and simulation of solar water heater: A TRNSYS perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 126-143.

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