| 基于智能算法的多机PSS参数协调优化 |
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| 引用本文： | 葛业斌,张步涵,邵剑,李中成,毛承雄,李小平,孙建波,李淼,李大虎.基于智能算法的多机PSS参数协调优化[J].水电能源科学,2013,31(9):193-196. |
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| 作者姓名： | 葛业斌 张步涵 邵剑 李中成 毛承雄 李小平 孙建波 李淼 李大虎 |
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| 作者单位： | 华中科技大学 强电磁工程与新技术国家重点实验室， 湖北 武汉 430074;华中科技大学 强电磁工程与新技术国家重点实验室， 湖北 武汉 430074;华中科技大学 强电磁工程与新技术国家重点实验室， 湖北 武汉 430074;华中科技大学 强电磁工程与新技术国家重点实验室， 湖北 武汉 430074;华中科技大学 强电磁工程与新技术国家重点实验室， 湖北 武汉 430074;华中科技大学 强电磁工程与新技术国家重点实验室， 湖北 武汉 430074;湖北电力调度通信中心， 湖北 武汉 430077;湖北电力调度通信中心， 湖北 武汉 430077;湖北电力调度通信中心， 湖北 武汉 430077 |
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| 基金项目： | 国家高技术研究发展计划（863计划）基金资助项目（2011AA05A101） |
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| 摘 要： | 针对大规模电力多机系统考虑多种运行方式变化下的PSS参数协调优化问题，提出一种将遗传算法寻优和BP神经网络计算阻尼比结合的智能算法。该算法根据机组对振荡模态参与因子的大小选择需要优化的机组，采用遗传算法进行不同振荡模态及运行方式下最小阻尼比最大化的寻优，并以BP神经网络获得阻尼比的时域仿真过程。在经典的四机两区域系统上仿真表明，该算法寻优效果良好，具有较好的鲁棒性。
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| 关 键 词： | 智能算法 PSS 参数优化 遗传算法 BP神经网络 |
Parameter Optimization of Multi-machine Power System Stabilizers Based on Intelligent Algorithm |
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| GE Yebin,ZHANG Buhan,SHAO Jian,LI Zhongcheng,MAO Chengxiong,LI Xiaoping,SUN Jianbo,LI Miao and LI Dahu.Parameter Optimization of Multi-machine Power System Stabilizers Based on Intelligent Algorithm[J].International Journal Hydroelectric Energy,2013,31(9):193-196. |
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| Authors: | GE Yebin ZHANG Buhan SHAO Jian LI Zhongcheng MAO Chengxiong LI Xiaoping SUN Jianbo LI Miao and LI Dahu |
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| Affiliation: | State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;Hubei Electric Power Dispatching and Communication Center, Wuhan 430077, China;Hubei Electric Power Dispatching and Communication Center, Wuhan 430077, China;Hubei Electric Power Dispatching and Communication Center, Wuhan 430077, China;Hubei Electric Power Dispatching and Communication Center, Wuhan 430077, China |
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| Abstract: | Aiming at the PSS coordinated parameter optimization of multi-machine system by considering operation mode change, an intelligent algorithm with combination of genetic algorithm and BP neural network is proposed to calculate damping ratio. Based on the participation factors of the oscillation modal, it selects the PSS need to be optimized. And then, genetic algorithm is used to maximize of minimum damping ratio in different oscillation mode and system operation mode. Finally, BP neural network is applied to get damping ratio in the time-domain simulation process. Simulation of two areas with four generators shows that the proposed algorithm has good optimization effect and robustness. |
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