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Performance prediction of solid desiccant – Vapor compression hybrid air-conditioning system using artificial neural network

Author

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  • Jani, D.B.
  • Mishra, Manish
  • Sahoo, P.K.

Abstract

In the present study, ANN (artificial neural network) model for a solid desiccant – vapor compression hybrid air-conditioning system is developed to predict the cooling capacity, power input and COP (coefficient of performance) of the system. This paper also describes the experimental test set up for collecting the required experimental test data. The experimental measurements are taken at steady state conditions while varying the input parameters like air stream flow rates and regeneration temperature. Most of the experimental test data (80%) are used for training the ANN model while remaining (20%) are used for the testing of ANN model. The outputs predicted from the ANN model have a high coefficient of correlation (R > 0.988) in predicting the system performance. The results show that the ANN model can be applied successfully and can provide high accuracy and reliability for predicting the performance of the hybrid desiccant cooling systems.

Suggested Citation

  • Jani, D.B. & Mishra, Manish & Sahoo, P.K., 2016. "Performance prediction of solid desiccant – Vapor compression hybrid air-conditioning system using artificial neural network," Energy, Elsevier, vol. 103(C), pages 618-629.
    • Handle: RePEc:eee:energy:v:103:y:2016:i:c:p:618-629
    DOI: 10.1016/j.energy.2016.03.014
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    Citations

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    Cited by:

    1. Jani, D.B. & Mishra, Manish & Sahoo, P.K., 2016. "Solid desiccant air conditioning – A state of the art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1451-1469.
    2. Tiezhu Sun & Xiaojun Huang & Caihang Liang & Riming Liu & Xiang Huang, 2022. "Prediction and Analysis of Dew Point Indirect Evaporative Cooler Performance by Artificial Neural Network Method," Energies, MDPI, vol. 15(13), pages 1-14, June.
    3. Shamim, Jubair A. & Hsu, Wei-Lun & Paul, Soumyadeep & Yu, Lili & Daiguji, Hirofumi, 2021. "A review of solid desiccant dehumidifiers: Current status and near-term development goals in the context of net zero energy buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    4. Harish Kumar Ghritlahre & Purvi Chandrakar & Ashfaque Ahmad, 2021. "A Comprehensive Review on Performance Prediction of Solar Air Heaters Using Artificial Neural Network," Annals of Data Science, Springer, vol. 8(3), pages 405-449, September.
    5. Harish Kumar Ghritlahre & Radha Krishna Prasad, 2018. "Development of Optimal ANN Model to Estimate the Thermal Performance of Roughened Solar Air Heater Using Two different Learning Algorithms," Annals of Data Science, Springer, vol. 5(3), pages 453-467, September.
    6. Ghritlahre, Harish Kumar & Prasad, Radha Krishna, 2018. "Application of ANN technique to predict the performance of solar collector systems - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 84(C), pages 75-88.
    7. Wu, X.N. & Ge, T.S. & Dai, Y.J. & Wang, R.Z., 2019. "Investigation on novel desiccant wheel using wood pulp fiber paper with high coating ratio as matrix," Energy, Elsevier, vol. 176(C), pages 493-504.
    8. Jani, D.B. & Mishra, Manish & Sahoo, P.K., 2017. "Application of artificial neural network for predicting performance of solid desiccant cooling systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 352-366.
    9. Ramadas Narayanan & Subbu Sethuvenkatraman & Roberto Pippia, 2022. "Energy and Comfort Evaluation of Fresh Air-Based Hybrid Cooling System in Hot and Humid Climates," Energies, MDPI, vol. 15(20), pages 1-13, October.
    10. Chen, W.D. & Vivekh, P. & Liu, M.Z. & Kumja, M. & Chua, K.J., 2021. "Energy improvement and performance prediction of desiccant coated dehumidifiers based on dimensional and scaling analysis," Applied Energy, Elsevier, vol. 303(C).
    11. Su, Minqi & Han, Xiaoqu & Dai, Yanbing & Wang, Jinshi & Liu, Jiping & Yan, Junjie, 2024. "Investigation on recirculated regenerative solid desiccant-assisted dehumidification system: Impact of system configurations and desiccant materials," Energy, Elsevier, vol. 286(C).
    12. Chung, Hyun Joon & Jeon, Yongseok & Kim, Dongwoo & Kim, Sunjae & Kim, Yongchan, 2017. "Performance characteristics of domestic hybrid dehumidifier combined with solid desiccant rotor and vapor compression system," Energy, Elsevier, vol. 141(C), pages 66-75.
    13. Gado, Mohamed G. & Ookawara, Shinichi & Nada, Sameh & El-Sharkawy, Ibrahim I., 2021. "Hybrid sorption-vapor compression cooling systems: A comprehensive overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).

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