Abstract
This paper proposes an improved simulated annealing for ball mill pulverizing system optimization of thermal power plan. The proposed algorithm combines the simulated annealing and Tabu search and for the annealing operations, the current calculated solution is evaluated according to the neighborhood of the values in Tabu list. Moreover, some rules for the generation of the neighborhood solution are presented based on the characteristics of the ball mill pulverizing system. The proposed algorithm is performed on the real field data. The results of the experiments verify that the proposed algorithm could determine the optimal values of process variables correctly and has faster convergence speed. In addition, the proposed algorithm has been put into practice and the statistic data show that the working time of ball mill pulverizing system is decreased and the energy consumption would be reduced.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Cheng, Q., Wang, Y.: The overview on the development of control techniques on intermediate storage bunker ball mill pulverizing system of power plant. Journal of Shanghai University of Electric Power 22(1), 48–54 (2006)
Wei, J., Wang, J., Guo, S.: Mathematic modeling and condition monitoring of power station tube-ball mill systems. In: 2009 American Control Conference, St. Louis, MO, USA, June 10-12, pp. 4699–4704 (2009)
Luo, Y., Jia, L., Cai, W., Liu, H.: Set-point optimization and control of coal-pulverizing systems with ball-tube mil. In: The 4th IEEE Conference on Industrial Electronics and Applications, Xi’an, China, May 25-27, pp. 1690–1694 (2009)
Li, X., Zeng, Y., Sun, J., Li, Y., Wu, H.-Y.: Fuzzy optimization control system and its application in ball mill pulverizing system. In: The 15th IEEE International Conference on Fuzzy Systems, Vancouver, BC, Canada, July 16-21, pp. 615–620 (2006)
Hao, Y., Yu, X., Zhao, G., Lv, Z.: Optimization for ball mill operation based on improved particle swarm optimization algorithm. Journal of Southeast University (Natural Science Edition) 38(3), 419–423 (2008)
Wang, H., Jia, M.-P., Huang, P., Chen, Z.-L.: A study on a new algorithm to optimize ball mill system based on modeling and GA. Energy Conversion and Management 51(4), 846–850 (2010)
Ribeiro, G.M., Mauric, G.R., Lorenad, L.A.N.: A simple and robust Simulated Annealing algorithm for scheduling workover rigs on onshore oil fields. Computers & Industrial Engineering 60(4), 519–526 (2011)
Han, S.-M., Chung, K.-H., Kim Balho, H.: ISO Coordination of Generator Maintenance Scheduling in Competitive Electricity Markets using Simulated Annealing. Journal of Electrical Engineering & Technology 6(4), 431–438 (2011)
Zain, A.M., Haron, H., Sharif, S.: Genetic algorithm and simulated annealing to estimate optimal process parameters of the abrasive waterjet machining. Engineering with Computers 27(3), 251–259 (2011)
Elmi, A., Solimanpur, M., Topaloglu, S., Elmi, A.: A simulated annealing algorithm for the job shop cell scheduling problem with intercellular moves and reentrant parts. Computers & Industrial Engineering 61(1), 171–178 (2011)
Jia, L., Li, X.: Self-optimization combined with fuzzy logic control for ball mill. International Journal of Computers, Systems and Signals 1(2), 231–239 (2000)
Chai, T., Yue, H.: Multivariable intelligent decoupling control system and its application. Acta Automatica Sinica 31(1), 123–131 (2005)
Hanafi, S., Yanev, N.: Tabu search approaches for solving the two-group classification problem. Annals of Operations Research 183(1), 25–46 (2011)
Suykens, J.A.K., Van Gestel, T., De Brabanter, J., De Moor, B., Vandewalle, J.: Least Squares Support Vector Machines. World Scientific Publishing Co. Pvt. Ltd., Singapore (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cao, H., Jia, Lx., Si, Gq., Zhang, Yb. (2012). An Improved Simulated Annealing for Ball Mill Pulverizing System Optimization of Thermal Power Plant. In: Zeng, D. (eds) Advances in Information Technology and Industry Applications. Lecture Notes in Electrical Engineering, vol 136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-26001-8_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-26001-8_19
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-26000-1
Online ISBN: 978-3-642-26001-8
eBook Packages: EngineeringEngineering (R0)