中文摘要：

同步发电机参数频域辨识方法一般假设小扰动条件下励磁电压保持不变，但实际上，试验过程中励磁电压不断变化，扰动大小的划分也带有一定经验性。为此，提出了基于蚁群算法的同步发电机参数改进频域辨识方法，该方法需要实时测量扰动后的发电机功角、定子电压、电流以及励磁电压等变量，并应用快速傅里叶变换及功率谱算法将各电气量转换为频域信号。然后，在计及励磁电压变化的条件下，应用蚁群优化算法拟合发电机电压q轴分量的频域特性，从而辨识d轴最优参数。q轴运算电抗不受励磁电压影响，故可按照传统方法辨识q轴参数。对某电站水轮发电机的参数辨识验证了改进频域方法的有效性，与传统方法相比．改进频域辨识方法可适用于较大扰动的情况，且d轴参数辨识精度较高，收敛性更好，具有较好的实用性。

英文摘要：

It is usually assumed that the generator is working under small disturbances and the excitation voltage remained constant in the frequency domain synchronous generator parameters identification. In fact, the classifieations of small and large disturbances are empirical and the excitation voltage keeps changing during the test. An ant colony optimization-hased improved frequency domain synchronous generator parameters identification method is proposed in this paper to solve these problems. The rotor angle, stator voltage ＆ current, excitation voltage of synchronous generator are measured. The fast Fourier transformation and frequency spectral analysis are used to analyze these variables in frequency domain. Then, the ant colony optimization algorithm is used in the curve fitting of frequently and amplitude characteristics of the stator voltage in quadrature axis. The direct axis parameters are identified with the excitation voltage variation taken into t~onsideration. The calculating reactance of quadrature axis is not influenced by the excitation voltage. So the quadrature axis parameters eould be identified as the traditional method. To validate its effectiveness, this improved frequency domain method is applied in parameters identification of a hydraulic generator. Compared with the traditional method, the improved method is more suitable for sc.enarios of larger disturbances. The accuracy of direct axis parameters identifieation is better than the classical method. It has good convergence and practicability.