Chaotic Optimal Operation of Hydropower Station with Ecology Consideration
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Abstract
Traditional optimal operation of hydropower station usually has two problems. One is that the optimal algorithm hasn’t high efficiency, and the other is that the optimal operation model pays little attention to ecology. And with the development of electric power market, the generated benefit is concerned instead of generated energy. Based on the analysis of time-varying electricity price policy, an optimal operation model of hydropower station reservoir with ecology consideration is established. The model takes the maximum annual power generation benefit, the maximum output of the minimal output stage in the year and the minimum shortage of eco-environment demand as the objectives, and reservoir water quantity balance, reservoir storage capacity, reservoir discharge flow and hydropower station output and nonnegative variable as the constraints. To solve the optimal model, a chaotic optimization genetic algorithm which combines the ergodicity of chaos and the inversion property of genetic algorithm is exploited. An example is given, which shows that the proposed model and algorithm are scientific and feasible to deal with the optimal operation of hydropower station.
- J. D. C. Little, “The Use of Storage Water in a Hydroelectric System,” Operational Research, Vol. 3, No. 2, March 1955, pp. 187-197.
- Y. C. Zhang, F. S. Li, Y. F. Du, Y. F. Huang and S. Y. Xiong, “The Optimization of Hydropower Station Reservoir Dispatching,” in Chinese, Journal of Huazhong University of Science and Technology, Vol. 9, No. 6, December 1981, pp. 49-56.
- W. Y. Tan, S. X. Huang, J. M. Liu and S. X. Fang, “Application of Dynamic Programming in Optimizing the Regulation of Reservoirs of Hydroelectric Stations,” in Chinese, Journal of Hydraulic Engineering, Vol. 13, No. 135, July 1982, pp. 1-7.
- Q. Huang and Z. Q. Yan, “A Discussion on Methods of Long-Term Optimal Operation of Hydropower Stations Reservoir,” in Chinese, Journal of Hydro Electric Power, Vol. 3, No. 3, March 1987, pp. 1-7.
- G. W. Ma, “Study on Stochastic Optimum Problems for Multireservoir Hydroelectric Systems,” in Chinese, Jour- nal of Xi’an University of Technology, Vol. 7, No. 4, December 1988, pp. 65-74.
- D. G. Shao, X. Y. Song, J. Xia and Z. Q. Sun, “Research on Real-Time Optimal Flood Dispatching Model for Yanghe Reservoir,” in Chinese, Advances in Water Science, Vol. 10, No. 2, February 1999, pp. 135-139.
- J. Wan and H. Y. Chen, “A Study on Optimal Operation of Hydropower Group by Combined Model of Decomposition Coordination and Aggregation-Decomposition of Large System,” in Chinese, Journal of Hydroelectric Engineering, Vol. 15, No. 2, February 1996, pp. 41-50.
- S. Y. Chen and H. C. Zhou, “Fuzzy Optimal Decision Theory and Model of the Multistage and Multiobjective System,” in Chinese, Water Resources and Power, Vol. 9, No. 1, January 1991, pp. 9-17.
- W. Robin and S. Mohd, “Evaluation of Genetic Algorithms for Optimal Reservior Resources,” Journal of Water Resource Planning and Management, Vol. 125, No. 1, January 1999, pp. 25-33.
- G. W. Ma and L. Wang, “Application of a Genetic Algorithm to Optimal Operation of Hydropower Station,” in Chinese, Advances in Water Science, Vol. 8, No. 3, March 1997, pp. 275-280.
- T. S. Hu, Y. H. Wan and S. Y. Feng, “Research on the Artificial Neural Network Methodology for Multi-Reservoir Operating Rules,” in Chinese, Advances in Water Science, Vol. 6, No. 1, January 1991, pp. 9-17.
- S. H. Zhang, Q. Huang, H. S. Wu and J. X. Yang, “A Modified Particle Swarm Optimizer for Optimal Operation of Hydropower Station,” in Chinese, Journal of Hydroelectric Engineering, Vol. 26, No. 1, January 1996, pp. 41-50.