A novel non-linear programming-based coal blending technology for power plants

Chemical Engineering Research and Design

Volumn 78, Issue 1, 2000, Pages 118-124

  Yin, Chungen ^a   Zhongyang, L ^a   Zhou, Junhu ^a   Cen, Kefa ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Back propagation; Coal blending; Linear programming; Neural networks; Nonlinear programming; Optimization design

Indexed keywords

BACKPROPAGATION; BLENDING; FOSSIL FUEL POWER PLANTS; NEURAL NETWORKS; NONLINEAR PROGRAMMING;

COAL BLENDING;

COAL PREPARATION;

BLENDING;

EID: 0342369488     PISSN: 02638762     EISSN: None     Source Type: Journal    
DOI: 10.1205/026387600526951     Document Type: Article

References (19)

1. Walz, M. A., Edeal, P. E. D. and Snow, J. S., 1995, Mixing it up - Coal blending in the 90s, Coal, 100(4): 63-65.
2. Arnold, B. J. and Smith, D. B., 1994, Coal blending: meeting specifications, Mining Engineering, 14(2): 327-33.
3. Cheng, Y. Q., Du, M. H., Li, W. H. and Xu, Z. G., 1997, Integrated optimum blending of steam coal is the clean coal technology suitable for Chinese coal combustion status, Clean Coal Technology (China), 3(1): 9-12, 27.
4. Jiang, F. and Xia, Y. C., 1997, Development routine and counter-measure of steam coal blending, Clean Coal Technology (China), 3(2): 14-16, 58.
5. Pongpirodom, P., 1994, On-line analysis for coal blending at Mae Moh mine, Thailand, Bulk Solids Handling, 14(2): 327-330.
6. Qiu. J. R., Ma, Y. Y., Zeng, H. C. and Guo, J., 1998, Comprehensive research on combustion characteristics of blended coal, Power Engineering, 13(5): 32-36 (in Chinese).
7. Yin. C. G., 1998, Application of non-linear theories to clean coal combustion technology, Ph D Dissertation, (Zhejiang University, Hangzhou (in Chinese)).
8. Chen, J., 1999, Studies on technology of coal blending and catalytic clean combustion, MS Thesis, (Zhejiang University, Zhejiang University, Hangzhou (in Chinese)).
9. Yin, C. G., Zhou, J. H., Luo, Z. Y., Yao, Q., Cao, X. Y., Tang, L. H., Wu, X. R. and Cen, K. F., 1997, Application of non-linear programming combined with artificial neural network method in coal blending - (II) Application demonstration, Journal of China Coal Society, 22(4): 343-348.
10. Tang, L. H., Zhou, J. H., Yao, Q., Cao, X. Y., Wu, X. R., Cao, D. Q., Yin, C. G. and Cen K.F., 1997, Nonlinear-programming mathematical modeling of coal blending for power plant, Proc 14th Annual Int Pittsburgh Coal Con & Workshop, Taiyuan, China.
11. Artos, V. and Scaroni, A. W., 1993, T.g.a. and drop-tube reactor studies of the combustion of coal blends, Fuel, 72(7): 927-933.
12. Sakurovs, R., Lynch, L. J. and Maher, T. P., 1994, The prediction of the fusibility of coal blends, Fuel Processing Technology, 37: 255-269.
13. x emission and burnout, Fuel, 73(9): 1447-1452.
14. Brown, D. W., Atkin, B. P., Miles, N. J. and Creasey, D. S., 1997, Determination of the handleability of a coal blend using an extrusion trough, Fuel, 76(13): 1183-1185.
15. Sarkar, D., 1995, Methods to speed up error back-propagation learning algorithm, ACM Computing Survey, 27(4): 519-542.
16. Yin, C. G., Luo, Z. Y., Ni, M. J. and Cen, K. F., 1998, Predicting coal ash fusion temperature with a back-propagation neural network model, Fuel, 77(15): 1777-1782.
17. Chen, W. M. and Jiang, N., 1996, Relation between the coal ash composition and fusibility, Clean Coal Technology, 2(2), 34-37 (in Chinese).
18. Fu, W. B. and Zhang, E. Z., 1993, A general correlation between non-homogeneous phase ignition temperature of coke and coal category and discrimination indexes, Power Engineering, 13(3): 34-42 (in Chinese).
19. Yu, J. and Zhou, J., 1989, Optimization Methods Programs Library -Principles and Instructions, (Mechanical Industry Press, Beijing) (in Chinese).