基于改进萤火虫算法的水电站群优化调度
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摘要
为探讨水电站群优化调度新方法,在标准萤火虫算法原理的基础上,引入了隔代大步长纯随机游走、优势保留和变异机制等寻优机制,提出了改进的萤火虫算法。以黑河梯级水电站群为应用实例,建立和求解了梯级发电量最大的中长期优化调度模型,获得了如下结论:(1)梯级发电量最大时,龙头水库水位呈丰水期快速蓄满、维持高水头运行、枯水期缓慢下降至死水位的变化规律;(2)由参数敏感性分析得到了扰动因子、荧光吸收因子和随机搜索间隔代数的最优值;(3)不同算法的对比分析说明IFA的准确性、稳定性、寻优能力均最优。研究成果对于指导黑河梯级水电站经济运行具有重要的实际意义。
To explore a new method for solving the optimal operation problem of a hydropower station group, this paper presents an improved firefly algorithm(IFA) that adopts the large-scale random walk, dominant reservation, and mutation mechanism. A mid-long term optimal operation model of maximal cascade power generation is developed and solved using IFA in a case study of the Heihe hydropower station group. The following conclusions are obtained:(1) When the power generation is maximized, the leading reservoir is filled up rapidly in high water season and maintains a high stage operation, and the reservoir stage goes down gradually to the dead water level in the dry season.(2) Optimal values of a disturbance factor, a fluorescence absorption factor, and stochastic search interval algebra are obtained using parameter sensitivity analysis.(3) Compared with two other algorithms, IFA is better in accuracy, stability, and optimization ability. The results are practically significant to the operation of the Heihe cascade hydropower stations.
To explore a new method for solving the optimal operation problem of a hydropower station group, this paper presents an improved firefly algorithm(IFA) that adopts the large-scale random walk, dominant reservation, and mutation mechanism. A mid-long term optimal operation model of maximal cascade power generation is developed and solved using IFA in a case study of the Heihe hydropower station group. The following conclusions are obtained:(1) When the power generation is maximized, the leading reservoir is filled up rapidly in high water season and maintains a high stage operation, and the reservoir stage goes down gradually to the dead water level in the dry season.(2) Optimal values of a disturbance factor, a fluorescence absorption factor, and stochastic search interval algebra are obtained using parameter sensitivity analysis.(3) Compared with two other algorithms, IFA is better in accuracy, stability, and optimization ability. The results are practically significant to the operation of the Heihe cascade hydropower stations.
引文
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[19]黄凯,周永权.带交尾行为的混沌人工萤火虫优化算法[J].计算机科学,2012,39(3):231-234.HUANG Kai,ZHOU Yongquan.Chaotic artificial glowworm swarm optimization algorithm with mating behavior[J].Computer Science,2012,39(3):231-234.(in Chinese)
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[22]黄强,刘晓黎,杨菊香,等.洮河九甸峡水库优化调度研究[J].水力发电学报,2008,27(2):17-21.HUANG Qiang,LIU Xiaoli,YANG Juxiang,et al.Study on the optimal operation of Taohe Jiudianxia Reservior[J].Journal of Hydroelectric Engineering,2008,27(2):17-21.(in Chinese)
[2]万新宇,王光谦.基于并行动态规划的水库发电优化[J].水力发电学报,2011,30(6):166-170.WAN Xinyu,WANG Guangqian.Parallel dynamic programming for hydropower generation optimization[J].Journal of Hydroelectric Engineering,2011,30(6):166-170.(in Chinese)
[3]赵铜铁钢,雷晓辉,陈云钟,等.水库调度决策单调性与动态规划算法改进[J].水利学报,2012,43(4):414-421.ZHAO Tongtiegang,LEI Xiaohui,CHEN Yunzhong,et al.Monotonicity in operation decision of reservoir and improved dynamic programming algorithm[J].Journal of Hydraulic Engineering,2012,43(4):414-421.(in Chinese)
[4]喻杉,纪昌明,杨子俊,等.基于逐步优化算法的水库预报预泄规则拟定研究[J].水力发电,2011,38(2):57-60.YU Shan,JI Changming,YANG Zijun,et al.Research on making forecast and pre-discharge rules for hydropower station based on progressive optimality algorithm[J].Water Power,2011,38(2):57-60.(in Chinese)
[5]纪昌明,蒋志强,孙平,等.基于判别式法及逐步优化算法的梯级蓄能调度图研究[J].水力发电学报,2014,33(3):118-125.JI Changming,JIANG Zhiqiang,SUN Ping,et al.Study on cascade energy storage dispatching figure based on discriminant criterion method and progressive optimality algorithm[J].Journal of Hydroelectric Engineering,2014,33(3):118-125.(in Chinese)
[6]Bai T,Kan Y B,Chang J X,et al.Fusing feasible search space into PSO for multi-objective cascade reservoir optimization[J].Applied Soft Computing,2017,51(C):328-340.
[7]Saberchenari K,Abghari H,Tabari H.Application of PSOalgorithm in short-term optimization of reservoir operation[J].Environmental Monitoring&Assessment,2016,188(12):667.
[8]白涛,黄强.蜂群遗传算法及在水库群优化调度中的应用[J].水电自动化与大坝监测,2009,33(1):1-4.BAI Tao,HUANG Qiang.Bee-swarm genetic algorithm and its application in optimal operation of group reservoirs[J].Hydropower Automation&Dam Monitoring,2009,33(1):1-4.(in Chinese)
[9]明波,黄强,王义民,等.基于改进布谷鸟算法的梯级水库优化调度研究[J].水利学报,2015,46(3):341-349.MING Bo,HUANG Qiang,WANG Yimin,et al.Cascade reservoir operation optimization based-on improved Cuckoo Search[J].Journal of Hydraulic Engineering,2015,46(3):341-349.(in Chinese)
[10]原文林,万芳,吴泽宁,等.梯级水库发电优化调度的改进粒子群算法应用研究[J].水力发电学报,2012,31(2):33-37,164.YUAN Wenlin,WAN Fang,WU Zening,et al.Application of improved particle swarm algorithm to optimized operation of cascade reservoir power generation[J].Journal of Hydroelectric Engineering,2012,31(2):33-37,164.(in Chinese)
[11]Yang X S.Firefly algorithms for multimodal optimization[C].5th International Symposium on Stochastic Algorithms-Foundations and Applications,2009,5792:169-178.
[12]陈恺,陈芳,戴敏,等.基于萤火虫算法的二维熵多阈值快速图像分割[J].光学精密工程,2014,22(2):517-523.CHEN Kai,CHEN Fang,DAI Min,et al.Fast image segmentation with multilevel threshold of two-dimensional entropy based on firefly algorithm[J].Optics&Precision Engineering,2014,22(2):517-523.(in Chinese)
[13]刘鹏,刘弘,郑向伟,等.基于改进萤火虫算法的动态自动聚集路径规划方法[J].计算机应用研究,2011,28(11):4146-4149.LIU Peng,LIU Hong,ZHENG Xiangwei,et al.Approach for dynamic group automatic aggregation path planning based on improved FA[J].Application Research of Computers,2011,28(11):4146-4149.(in Chinese)
[14]杜晓刚,党建武,王阳萍,等.基于萤火虫算法的互信息医学图像配准[J].计算机科学,2013,40(7):273-276.DU Xiaogang,DANG Jianwu,WANG Yangping,et al.Mutual information medical image registration based on firefly algorithm[J].Computer Science,2013,40(7):273-276.(in Chinese)
[15]Jati G K,Suyanto.Evolutionary discrete firefly algorithm for travelling salesman problem[C].2nd International Conference on Adaptive and Intelligent Systems.2011,6934:393-403.
[16]Kazem A,Sharifi E,Hussain F K,et al.Support vector regression with chaos-based firefly algorithm for stock market price forecasting[J].Applied Soft Computing,2013,13(2):947-958.
[17]Othman M M,El-Khattam W,Hegazy Y G,et al.Optimal placement and sizing of voltage controlled distributed generators in unbalanced distribution networks using supervised firefly algorithm[J].International Journal of Electrical Power&Energy Systems,2016,82:105-113.
[18]刘长平,叶春明.具有混沌搜索策略的萤火虫优化算法[J].系统管理学报,2013,22(4):538-543.LIU Changping,YE Chunming.Firefly algorithm with chaotic search strategy[J].Journal of Systems&Management,2013,22(4):538-543.(in Chinese)
[19]黄凯,周永权.带交尾行为的混沌人工萤火虫优化算法[J].计算机科学,2012,39(3):231-234.HUANG Kai,ZHOU Yongquan.Chaotic artificial glowworm swarm optimization algorithm with mating behavior[J].Computer Science,2012,39(3):231-234.(in Chinese)
[20]Coelho L D,Mariani V C.Improved firefly algorithm approach applied to chiller loading for energy conservation[J].Energy and Buildings,2013,59:273-278.
[21]Garousi-Nejad I,Bozorg-Haddad O,Loaiciga H A,et al.Application of the firefly algorithm to optimal operation of reservoirs with the purpose of irrigation supply and hydropower production[J].Journal of Irrigation and Drainage Engineering,2016,142(10):04016041.
[22]黄强,刘晓黎,杨菊香,等.洮河九甸峡水库优化调度研究[J].水力发电学报,2008,27(2):17-21.HUANG Qiang,LIU Xiaoli,YANG Juxiang,et al.Study on the optimal operation of Taohe Jiudianxia Reservior[J].Journal of Hydroelectric Engineering,2008,27(2):17-21.(in Chinese)