| 引用本文: | 刘昌玉,何雪松,李崇威,王 湛,张恩博,颜秋容.用于水轮机-引水管道参数辨识的改进型人工鱼群算法[J].电力自动化设备,2013,33(11): |
| LIU Changyu,HE Xuesong,LI Chongwei,WANG Zhan,ZHANG Enbo,YAN Qiurong.Improved artificial fish swarm algorithm for parameter identification of hydroelectric turbine-conduit system[J].Electric Power Automation Equipment,2013,33(11): |
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| 摘要: |
| 提出了一种融合蚁群算法的改进型人工鱼群算法，对水轮机-引水管道系统进行参数辨识。该算法在每次迭代中先应用鱼群算法对搜索空间进行全局搜索，然后以当代全局最优解为基础利用蚁群算法对其领域进行局部搜索。根据现场实测数据，所提算法通过最小化目标函数辨识出了水轮机-引水管道模型参数。基于实测数据的建模结果表明，与传统辨识方法相比，所提算法具有更好的全局优化能力和鲁棒性能。 |
| 关键词: 水轮机 引水管道 参数辨识 人工鱼群算法 蚁群优化算法 建模 仿真 |
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| Improved artificial fish swarm algorithm for parameter identification of hydroelectric turbine-conduit system |
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LIU Changyu1, HE Xuesong1, LI Chongwei1, WANG Zhan2, ZHANG Enbo2, YAN Qiurong3
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1.School of Hydropower and Information Engineering，Huazhong University of Science and Technology，Wuhan 430074，China;2.Northeast China Electric Power Research Institute，Shenyang 110006，China;3.College of Electrical and Electronic Engineering，Huazhong University of Science and Technology，Wuhan 430074，China
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| Abstract: |
| An improved artificial fish swarm algorithm combined with ant colony optimization is presented for the parameter identification of hydroelectric turbine-conduit system，which applies the artificial fish swarm algorithm to globally explore the search space in each iteration cycle and then employs the ant colony optimization to locally search the domain with the currently best solution. Based on the data measured on site，it identifies the parameters of hydroelectric turbine-conduit model by minimizing the object function. The modeling results based on site data show that，compared with the traditional identification methods，the proposed algorithm has better global optimization ability and robustness. |
| Key words: hydroelectric turbines conduit parameter identification artificial fish swarm algorithm ant colony optimization algorithm model buildings computer simulation |
