Development and application of hourly building cooling load prediction model

2010 International Conference on Advances in Energy Engineering, ICAEE 2010

Volumn , Issue , 2010, Pages 392-395

  Li, Qiong ^a   Meng, Qinglin ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BUILDING COOLING LOAD; COOLING LOAD; PREDICTION MODEL;

AIR CONDITIONING; COOLING; FORECASTING; MATHEMATICAL MODELS; OFFICE BUILDINGS;

NEURAL NETWORKS;

EID: 77958000513     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICAEE.2010.5557536     Document Type: Conference Paper

References (12)

1. M.S. Sodha, B. Kaur, A Kumar and N.K. Bansal, "A comparison of the admittance and fourier methods for predicting heating/cooling loads," Solar Energy, vol. 36, pp. 125-127, 1986.
2. J.S. Greg and AK. Robert, "A correlation method for predicting monthly and armual cooling loads in direct gain passive solar heated buildings," Energy Conversion and Management, vol. 29, pp. 175-187, 1989.
3. M. Bauer and J.L. Scartezzini, "A simplified correlation method accounting for heating and cooling loads in energyefficient buildings," Energy and Buildings, vol. 27, pp. 147-154, 1998.
4. O. M.A. AI-Rabghi and K. M. AI-Johani, "Utilizing transfer function method for hourly cooling load calculation," Energy Conversion and Management, vol. 38, pp. 319-332,1997.
5. A E. Ben-Nakhi and M. A Mahmoud, "Cooling load prediction for buildings using general regression neural networks," Energy Conversion and Management, vol 45, pp. 2127-2141,2004.
6. K.W. Mui and L.T. Wong, "Cooling load calculations in subtropical climate," Building and Environment, vol. 42, pp. 2498-2504,2007.
7. S. A Kalogiron, "Artificial neural networks in renewable energy systems applications: a review," Renewable and Sustainable Energy Reviews, vol. 5, pp. 373-400, 2001.
8. J. Yang, H. Rivard and R. Zmeureann, "On-line building energy prediction using adaptive artificial neural networks," Energy and Buildings, vol. 37, pp. 1250-1259,2005.
9. P. A Gonzalez and J. M. Zamarrefio, "Prediction of hourly energy consumption in buildings based on a feedback artificial neural network," Energy and Buildings, vol. 37, pp. 595-601, 2005.
10. Q. Li, Q. Meng, J. Cai, H. Yoshino and A Mochida, "Applying support vector machine to predict hourly cooling load in the building," Applied Energy, vol. 86, pp. 2249-2256, 2009.
11. Q. Li, Q. Meng, J. Cai, H. Yoshino and A Mochida, "Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks," Energy Conversion and Management, vol. 50, pp. 90-96, 2009.
12. DeST 20051028, University of Tsinghua University, China