Imperial College London
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Professor Yujian Ye

Faculty of Engineering, Department of Electrical and Electronic Engineering

Honorary Lecturer
 
 
 
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Contact

 

yujian.ye11

 
 
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Location

 

1105Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Hu:2024:10.1109/TPWRS.2023.3240826,
author = {Hu, J and Wang, Q and Ye, Y and Wu, Z and Tang, Y},
doi = {10.1109/TPWRS.2023.3240826},
journal = {IEEE Transactions on Power Systems},
pages = {877--889},
title = {A High Temporal-Spatial Resolution Power System State Estimation Method for Online DSA},
url = {http://dx.doi.org/10.1109/TPWRS.2023.3240826},
volume = {39},
year = {2024}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The rapidly increasing integration of renewable energy sources aggravates the uncertainty and fluctuation in modern power system, which promotes the development of online dynamic security assessment (DSA). Real-time acquisition of high resolution temporal-spatial information on the system states lays the foundation for online DSA, while limited PMU installation and complex dynamic characteristics in real systems impose severe challenges to estimate system states with high quality in real time. This paper proposes a high temporal-spatial resolution state estimation (SE) method, leveraging graph convolutional network (GCN) and dense connectivity structure to estimate states of whole system at PMU reporting rate. Based on proposed SE method, an online DSA framework is developed for transient stability assessment (TSA), which only relies on the hybrid measurements accessible to the control centers in practice. Numerical experiment results in different scenarios demonstrate that the proposed SE method exhibits high SE accuracy and efficiency under different PMU observability. The performance improvement of SE-based TSA approach versus raw-measurements-based TSA approaches is also verified both theoretically and experimentally.
AU  - Hu,J
AU  - Wang,Q
AU  - Ye,Y
AU  - Wu,Z
AU  - Tang,Y
DO  - 10.1109/TPWRS.2023.3240826
EP  - 889
PY  - 2024///
SN  - 0885-8950
SP  - 877
TI  - A High Temporal-Spatial Resolution Power System State Estimation Method for Online DSA
T2  - IEEE Transactions on Power Systems
UR  - http://dx.doi.org/10.1109/TPWRS.2023.3240826
VL  - 39
ER  -
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