| 同步发电机动态参数辨识 |
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| 引用本文： | 米增强,陈志忠,南志远,马晋韬,金基圣,齐国顺,孟大伟.同步发电机动态参数辨识[J].中国电机工程学报,1998,18(2):100-105. |
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| 作者姓名： | 米增强 陈志忠 南志远 马晋韬 金基圣 齐国顺 孟大伟 |
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| 作者单位： | 1. 华北电力大学,北京,100085
2. 黑龙江省电力试验研究所,哈尔滨,150030 |
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| 摘 要： | 本文以发电机连续时间状态空间模型为研究对象，首次成功地实现了利用连续时间的修正扩展卡尔曼滤波（ＣＥＫＦ）在线辨识发电机的暂态和次暂态１１个参数；用一个简易可行的修正项加入到状态量对未知参数求偏导的公式中，使得算法即使在噪声统计特性有较大误差的情况下仍具有很高的无偏性；实现了电压解耦及用伪随机序列作为小扰动输入信号辨识发电机的参数；成功地寻找出了算法中所需初值；对新信息、方程系数、参数进行了跟踪，并
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| 关 键 词： | 同步发电机 电机 模型 参数 发电机 动态参数 |
Dynamic Parameter Identification of Synchronous Machines |
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| Mi Zengqiang,Cheng Zhizhong,Nan Zhiyuan,Ma Jintao,Jin Jisheng,Qi Guoshun,Meng Dawei.Dynamic Parameter Identification of Synchronous Machines[J].Proceedings of the CSEE,1998,18(2):100-105. |
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| Authors: | Mi Zengqiang Cheng Zhizhong Nan Zhiyuan Ma Jintao Jin Jisheng Qi Guoshun Meng Dawei |
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| Affiliation: | Mi Zengqiang\ Cheng Zhizhong\ Nan Zhiyuan\ Ma Jintao (Beijing Graduate School of North China Electrical Power University) Jin Jisheng\ Qi Guoshun\ Meng Dawei (Electrical Power Research Institute of Heilongjiang Province) |
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| Abstract: | In this paper,corrected EKF is applied for dynamic parameter identification of synchronous machine on line.Eleven parameters of synchronous machines are identified successfully.A simple corrected item is added to the algorithm of CEKF,which makes the algorithm more advantageous than before.Decoupled method and pseudorandom binary sequence (PRBS) used as input disturbance.Initial values and the optimum corrected step have been given in this paper.On line parameters identification of generators in laboratory and in real field is implemented,and the results are satisfactory. The algorithms and formulas are strictly proved.The results of simulation have shown that these methods used in this paper are achieved in accuracy and the wide range of initial values. |
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| Keywords: | synchronous machine model and parameter corrected extended kalman filter least square on line identification |
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