An Improved Contract Net Protocol with Multi-Agent for Reservoir Flood Control Dispatch

Wei Huang, Xingnan Zhang, Xiaodong Wei

.

DOI: 10.4236/jwarp.2011.310084                

Abstract

Contract Net Protocol (CNP) has been widely used in solving the problems of multi-Agent cooperates and reservoir flood control optimization dispatch. This paper designs an Agent functional module based on the multi-Agent coordinated the construction of reservoir flood control optimization dispatch and the corresponding Agent to solve the problem of classical CNP in the Agent communication aspect, to enhance the efficiency of reservoir optimization dispatch and to improve the insufficiency of the classical CNP in the application of reservoir flood control dispatcher. Then, the capacity factor and the cooperation level are introduced in the module. Experiments are conducted on the Agentbuilder simulation platform to simulate reservoir flood control optimization dispatching with the improved CNP. The simulation results show the communication interactive efficiency and the performance of new protocol is superior to those of the classical CNP.

Keywords

Flood Control Scheduling, Reservoir Dispatch, Agent, Multi-Agent, CNP

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	M. J. Wooldridge and N. R. Jennings, “Intelligent Agent: Theory and Practice” Knowledge Engineering Review, Vol. 10, No. 2, 1995, pp. 115-152. doi:10.1017/S0269888900008122
[2]	X. Yang, S.-Q. Xu and F.-X. Meng, “Reservoir Optimal Operation and Development Trend Research,” Journal of Heilongjiang Hydraulic Engineering, Vol. 37, No. 1, 2010, pp. 40-42.
[3]	S. Parsons and N. R. Jennings, “Negotiation through Argumentation—A Preliminary Report,” In: V. R. Lesser, Ed., Proceedings of the International Conference on Multi-Agent System, Tokto, 1996, pp. 267-274.
[4]	Z. Z. Huang and Z. H. Zhou, “Study on the Large-Scale and Multi-Objective Decision Making Model of Multi- Reservoir Systems for Real-Time Flood Operation,” International Journal Hydroelectric Energy, Vol. 4, No. 3, 1994, pp. 51-59.
[5]	X. M. Xie and S. Y. Chen, “Fuzzy Optimizing Dispatching Model for Multi-Reservoir Power System and Interaction Balance—Fuzzy Programming Method,” Advances in Water Science, Vol. 5, No. 3, 1995, pp. 189-197.
[6]	Y. W. Tan and S. X. Huang, “Optimizing Dispatching of the Hydroelectric Power Station Reservoir Based on the Stochastic Dynamic Programming Method,” Journal of Hydraulic Engineering, Vol. 27, No. 7, 1982, pp. 1-7.
[7]	S. Ko, D. G. Fontane and J. W. Labadie, “Multi-Objective Optimization of Reservoir Systems Operation,” Water Resources Bulletin, Vol. 28, No.1, 1992, pp. 111-127.
[8]	S. Vedula and D. N. Kumar, “An Integrated Model for Optimal Reservoir Operation for Irrigation of Multiple Crops,” Water Resources Research, Vol. 32, No. 4, 1996, pp. 1101-1108. doi:10.1029/95WR03110
[9]	J. S. Zhao, “Study on Holistic Model for Optimization of Water Resources Allocation Based on Complex Adaptive System Theory,” Ph.D. Thesis, Tsinghua University, Beijing, 2003.
[10]	B. Malekmohammadi, B. Zahraie and R. Kerachian, “Ranking Solutions of Multi-Objective Reservoir Operation Optimization Models Using Multi-Criteria Decision Analysis,” Expert Systems with Applications, Vol. 38, No. 6, 2011, pp.7851-7863. doi:10.1016/j.eswa.2010.12.119
[11]	T. S. Hu, P. Yuan and J. Ding, “Applications of Artificial Neural Network to Hydrology and Water Resources,” Advances in water science, Vol. 6, No. 1, 1995, pp. 76- 82.
[12]	X. A. Wang and C. J. Li, “Research and Application of Genetic Algorithm to Cascade Hyroelectric Stations’ Short-Term Optimization Scheduling” Journal of Yangtze River Scientific Research Institute, Vol. 20, No. 3, 2003, pp. 13-15.
[13]	R. G. Smith, “The CNP: High-Level Communication and Control in a Distributed Problem Solver,” IEEE Transaction on Computers, Vol. 29, No. 12, 1980, pp. 1104-1113. doi:10.1109/TC.1980.1675516
[14]	L. Yannis and F. Tim, “Semantic and Conversations for an Agent Communication Language,” Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Nagoyo, 1997, pp. 23-29.