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Performance prediction of a direct expansion solar assisted heat pump using artificial neural networks

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  • Mohanraj, M.
  • Jayaraj, S.
  • Muraleedharan, C.

Abstract

This paper presents the suitability of artificial neural network (ANN) to predict the performance of a direct expansion solar assisted heat pump (DXSAHP). The experiments were performed under the meteorological conditions of Calicut city (latitude of 11.15 °N, longitude of 75.49 °E) in India. The performance parameters such as power consumption, heating capacity, energy performance ratio and compressor discharge temperature of a DXSAHP obtained from the experimentation at different solar intensities and ambient temperatures are used as training data for the network. The back propagation learning algorithm with three different variants (such as, Lavenberg-Marguardt (LM), scaled conjugate gradient (SCG) and Pola-Ribiere conjugate gradient (CGP)) and logistic sigmoid transfer function were used in the network. The results showed that LM with 10 neurons in the hidden layer is the most suitable algorithm with maximum correlation coefficients (R2) of 0.999, minimum root mean square (RMS) value and low coefficient of variance (COV). The reported results conformed that the use of ANN for performance prediction of DXSAHP is acceptable.

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  • Mohanraj, M. & Jayaraj, S. & Muraleedharan, C., 2009. "Performance prediction of a direct expansion solar assisted heat pump using artificial neural networks," Applied Energy, Elsevier, vol. 86(9), pages 1442-1449, September.
    • Handle: RePEc:eee:appene:v:86:y:2009:i:9:p:1442-1449
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    1. Wang, Zhangyuan & Guo, Peng & Zhang, Haijing & Yang, Wansheng & Mei, Sheng, 2017. "Comprehensive review on the development of SAHP for domestic hot water," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 871-881.
    2. Zhou, Jinzhi & Zhao, Xudong & Ma, Xiaoli & Qiu, Zhongzhu & Ji, Jie & Du, Zhenyu & Yu, Min, 2016. "Experimental investigation of a solar driven direct-expansion heat pump system employing the novel PV/micro-channels-evaporator modules," Applied Energy, Elsevier, vol. 178(C), pages 484-495.
    3. Yu, Xiaohui & Guo, Zhonglian & Gao, Zhi & Yang, Bin & Ma, Xiuqin & Dong, Shengming, 2023. "Thermodynamic investigation of a direct-expansion solar assisted heat pump with evacuated tube collector-evaporator," Renewable Energy, Elsevier, vol. 206(C), pages 418-427.
    4. Moreno-Rodriguez, A. & Garcia-Hernando, N. & González-Gil, A. & Izquierdo, M., 2013. "Experimental validation of a theoretical model for a direct-expansion solar-assisted heat pump applied to heating," Energy, Elsevier, vol. 60(C), pages 242-253.
    5. Li, Ning & Xia, Liang & Shiming, Deng & Xu, Xiangguo & Chan, Ming-Yin, 2012. "Dynamic modeling and control of a direct expansion air conditioning system using artificial neural network," Applied Energy, Elsevier, vol. 91(1), pages 290-300.
    6. Wahiba Yaïci & Michela Longo & Evgueniy Entchev & Federica Foiadelli, 2017. "Simulation Study on the Effect of Reduced Inputs of Artificial Neural Networks on the Predictive Performance of the Solar Energy System," Sustainability, MDPI, vol. 9(8), pages 1-14, August.
    7. Hao, Wengang & Zhang, Han & Liu, Shuonan & Mi, Baoqi & Lai, Yanhua, 2021. "Mathematical modeling and performance analysis of direct expansion heat pump assisted solar drying system," Renewable Energy, Elsevier, vol. 165(P1), pages 77-87.
    8. Mohanraj, M. & Jayaraj, S. & Muraleedharan, C., 2012. "Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1340-1358.
    9. Varun & Siddhartha, 2010. "Thermal performance optimization of a flat plate solar air heater using genetic algorithm," Applied Energy, Elsevier, vol. 87(5), pages 1793-1799, May.
    10. Gunasekar, N. & Mohanraj, M. & Velmurugan, V., 2015. "Artificial neural network modeling of a photovoltaic-thermal evaporator of solar assisted heat pumps," Energy, Elsevier, vol. 93(P1), pages 908-922.
    11. Cai, Baoping & Liu, Yonghong & Fan, Qian & Zhang, Yunwei & Liu, Zengkai & Yu, Shilin & Ji, Renjie, 2014. "Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network," Applied Energy, Elsevier, vol. 114(C), pages 1-9.
    12. Lazrak, Amine & Leconte, Antoine & Chèze, David & Fraisse, Gilles & Papillon, Philippe & Souyri, Bernard, 2015. "Numerical and experimental results of a novel and generic methodology for energy performance evaluation of thermal systems using renewable energies," Applied Energy, Elsevier, vol. 158(C), pages 142-156.
    13. Xu, Yingjie & Mao, Chengbin & Huang, Yuangong & Shen, Xi & Xu, Xiaoxiao & Chen, Guangming, 2021. "Performance evaluation and multi-objective optimization of a low-temperature CO2 heat pump water heater based on artificial neural network and new economic analysis," Energy, Elsevier, vol. 216(C).
    14. Huang, Wenzhu & Ji, Jie & Xu, Ning & Li, Guiqiang, 2016. "Frosting characteristics and heating performance of a direct-expansion solar-assisted heat pump for space heating under frosting conditions," Applied Energy, Elsevier, vol. 171(C), pages 656-666.
    15. Musawenkosi Lethumcebo Thanduxolo Zulu & Rudiren Pillay Carpanen & Remy Tiako, 2023. "A Comprehensive Review: Study of Artificial Intelligence Optimization Technique Applications in a Hybrid Microgrid at Times of Fault Outbreaks," Energies, MDPI, vol. 16(4), pages 1-32, February.
    16. Mohanraj, M. & Belyayev, Ye. & Jayaraj, S. & Kaltayev, A., 2018. "Research and developments on solar assisted compression heat pump systems – A comprehensive review (Part A: Modeling and modifications)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 90-123.
    17. Chua, K.J. & Chou, S.K. & Yang, W.M., 2010. "Advances in heat pump systems: A review," Applied Energy, Elsevier, vol. 87(12), pages 3611-3624, December.
    18. Stephen Tangwe & Patrick Mukumba & Golden Makaka, 2023. "An Installed Hybrid Direct Expansion Solar Assisted Heat Pump Water Heater to Monitor and Modeled the Energy Factor of a University Students’ Accommodation," Energies, MDPI, vol. 16(3), pages 1-30, January.
    19. Badiei, A. & Golizadeh Akhlaghi, Y. & Zhao, X. & Shittu, S. & Xiao, X. & Li, J. & Fan, Y. & Li, G., 2020. "A chronological review of advances in solar assisted heat pump technology in 21st century," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    20. 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.
    21. Omojaro, Peter & Breitkopf, Cornelia, 2013. "Direct expansion solar assisted heat pumps: A review of applications and recent research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 33-45.
    22. Khorasaninejad, Ehsan & Hajabdollahi, Hassan, 2014. "Thermo-economic and environmental optimization of solar assisted heat pump by using multi-objective particle swam algorithm," Energy, Elsevier, vol. 72(C), pages 680-690.
    23. Liu, Zengkai & Liu, Yonghong & Zhang, Dawei & Cai, Baoping & Zheng, Chao, 2015. "Fault diagnosis for a solar assisted heat pump system under incomplete data and expert knowledge," Energy, Elsevier, vol. 87(C), pages 41-48.

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