| 引用本文: | 徐 波,章林炜,俞向栋,等.基于系统辨识的电力系统惯量在线评估改进方法[J].电力系统保护与控制,2021,49(18):62-69.[点击复制] |
| XU Bo,ZHANG Linwei,YU Xiangdong,et al.An improved method of power system inertia online estimation based on system identification[J].Power System Protection and Control,2021,49(18):62-69[点击复制] |
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| 摘要: |
| 虽然基于系统辨识的惯量在线评估方法可以在线评估电力系统惯量，但是目前无法确定最佳的模型阶次，导致误差较大。为提升惯量在线评估的准确性，首先对电力系统正常运行条件下的实测数据进行信号预处理，防止噪声信息造成的过拟合现象，以提高抗噪声扰动能力。其次将发电机的有功功率变化量作为输入，频率波动作为输出，利用AIC准则确定系统辨识模型阶次，使用系统辨识方法建立合适的动态模型。然后利用辨识模型的阶跃响应计算系统惯量，避免惯量在线评估过程中对模型降阶引起的误差。最后，在Matlab/Simulink软件中搭建仿真系统，验证了所提方法的有效性和准确性。 |
| 关键词: 电力系统惯量 在线评估 系统辨识 模型阶次 阶跃响应 |
| DOI：DOI: 10.19783/j.cnki.pspc.201352 |
| 投稿时间：2020-11-05修订日期：2020-11-05 |
| 基金项目:国家自然科学基金项目资助(51977128)；上海市科学技术委员会项目资助(17020500800) |
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| An improved method of power system inertia online estimation based on system identification |
| XU Bo,ZHANG Linwei,YU Xiangdong,BIAN Xiaoyan,LI Dongdong |
| (School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China) |
| Abstract: |
| Although the online inertia estimation method based on system identification can estimate the inertia of the power system, it is unable to determine the best model order, leading to large errors. In order to improve the accuracy of online estimation of inertia, this paper first preprocesses the measured data under the normal operating conditions of a power system to prevent over-fitting caused by noise information and to improve the ability to resist noise disturbance. Secondly, the generator's active power change is taken as input, and frequency fluctuation is taken as output. The AIC criterion is used to determine the order of the system identification model, and the system identification method is used to establish a suitable dynamic model. Then the step response of the identification model is used to calculate the inertia of the system to avoid errors caused by the reduction of the model in the inertia online evaluation process. Finally, a simulation system is built in Matlab/Simulink to verify the effectiveness and accuracy of the proposed method.
This work is supported by the National Natural Science Foundation of China (No. 51977128) and the Project of Shanghai Science and Technology Commission (No. 17020500800). |
| Key words: power system inertia online estimation system identification order of the identification model step response |
