.png){kind=icon}
返回
PMU Based Problematic Parameter Identification Approach for Calibrating Generating Unit Models
.png){kind=icon}
OA
AI
DOI：10.1109/TIA.2021.3095831.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Accurate model of generating unit plays a key role in power system modeling and simulation. To ensure the safe and stable operation of power grids, North American Electric Reliability Corporation requires that all generators larger than 10 MVA have to perform the model verification in every five years. However, the traditional key parameter identification based model calibration method cannot guarantee the accurate correction of the generator's problematic parameters, which have errors with their real values. The effectiveness of this kind model calibration method is still in doubt. To address the issues, this article developed a problematic-parameter-identification based generating unit model calibration approach. Trajectory sensitivity based sensitivity analysis is applied to determine the problematic parameter candidates (PPCs), which determine the dynamic responses of the system. Then, the Hilbert spectrum of PPCs and model output error curves are compared in time-frequency domain to screen out the problematic parameters. Also, the selected problematic parameters are calibrated with the measurements based identification technique. The effectiveness of the proposed method has been validated throughout a series testing cases from an actual hydropower plant integrated power system.
Keyword:
Time-frequency analysis
Calibration
Analytical models
Generators
Parameter estimation
Trajectory
Sensitivity analysis
Generating unit model
parameter calibration
problematic parameter
sensitivity analysis
time-frequency analysis
期刊
IF:
4.5
论文数:
1.1W
被引数:
3.5W
机构
引用论文
Effect of varying polyglutamate chain length on the structure and stability of ferricytochrome c
.png){kind=icon}
PREAI
分享收藏Practical Considerations to Calibrate Generator Model Parameters Using Phasor Measurements使用相量测量校准发电机模型参数的实际考虑
PREAI
分享收藏Generator Dynamic Model Validation and Parameter Calibration Using Phasor Measurements at the Point of Connection在连接点使用相量测量进行发电机动态模型验证和参数校准
PREAI
分享收藏WECC Composite Load Model Parameter Identification Using Evolutionary Deep Reinforcement Learning
OAAI
OAAI分享收藏
查看更多内容