Data-Driven Short-Term Voltage Stability Assessment Based on Spatial-Temporal Graph Convolutional Network

03/05/2021
by   Yonghong Luo, et al.
0

Post-fault dynamics of short-term voltage stability (SVS) present spatial-temporal characteristics, but the existing data-driven methods for online SVS assessment fail to incorporate such characteristics into their models effectively. Confronted with this dilemma, this paper develops a novel spatial-temporal graph convolutional network (STGCN) to address this problem. The proposed STGCN utilizes graph convolution to integrate network topology information into the learning model to exploit spatial information. Then, it adopts one-dimensional convolution to exploit temporal information. In this way, it models the spatial-temporal characteristics of SVS with complete convolutional structures. After that, a node layer and a system layer are strategically designed in the STGCN for SVS assessment. The proposed STGCN incorporates the characteristics of SVS into the data-driven classification model. It can result in higher assessment accuracy, better robustness and adaptability than conventional methods. Besides, parameters in the system layer can provide valuable information about the influences of individual buses on SVS. Test results on the real-world Guangdong Power Grid in South China verify the effectiveness of the proposed network.

READ FULL TEXT

page 1

page 3

11/30/2020

TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting

Traffic flow forecasting is of great significance for improving the effi...
04/15/2022

Spatio-Temporal-Frequency Graph Attention Convolutional Network for Aircraft Recognition Based on Heterogeneous Radar Network

This paper proposes a knowledge-and-data-driven graph neural network-bas...
11/11/2017

3D Randomized Connection Network with Graph-based Label Inference

In this paper, a novel 3D deep learning network is proposed for brain MR...
05/27/2021

Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems

The Dynamic Pickup and Delivery Problem (DPDP) is aimed at dynamically s...
09/18/2022

Active Defense Analysis of Blockchain Forking through the Spatial-Temporal Lens

Forking breaches the security and performance of blockchain as it is sym...
07/26/2021

Short-Term Electricity Price Forecasting based on Graph Convolution Network and Attention Mechanism

In electricity markets, locational marginal price (LMP) forecasting is p...