Publications

You can also find my articles on my Google Scholar profile.

Training A Dynamic Neural Network to Detect False Data Injection Attacks Under Multiple Unforeseen Operating Conditions

Published in IEEE Transactions on Smart Grid, 2024

This paper is aimed at addressing the concept drift issue in power system measurements data while detecting FDIAs. It proposes an online self-adptive mechanism to accmodate the traditional attack detection model to unforeseen system operating points.

Recommended citation: Dongping Hu, Shengyang Wu, Jingyu Wang and Dongyuan Shi, "Training a Dynamic Neural Network to Detect False Data Injection Attacks Under Multiple Unforeseen Operating Conditions," IEEE Transactions on Smart Grid, vol. 15, no. 3, pp. 3248-3261.
Download Paper

Interpretable Detection and Localization of False Data Injection Attacks Based on Causal Learning

Published in 2023 IEEE Power & Energy Society General Meeting (PESGM), 2023

This paper propose a causal learning structure to quantify the casuality between measurements and locate the measurements under cyber attacks based on the causality anomalies.

Recommended citation: Shengyang Wu, Dongping Hu, Yi Gao, Dongyuan Shi and Jingyu Wang, "Interpretable Detection and Localization of False Data Injection Attacks Based on Causal Learning," 2023 IEEE Power & Energy Society General Meeting (PESGM), Orlando, FL, USA, 2023, pp. 1-5
Download Paper

Unveiling bidding uncertainties in electricity markets: A Bayesian deep learning framework based on accurate variational inference

Published in Energy, 2023

This paper uses a modified Bayesian Neural Network for the probalistic forecasting of bidding behaviors of generation companies and analyse the uncertainty within. It also provide a sensitivity analysis of the bidding behavior influencing factors.

Recommended citation: Shengyang Wu, Zhaohao Ding, Jingyu Wang and Dongyuan Shi, Unveiling bidding uncertainties in electricity markets: A Bayesian deep learning framework based on accurate variational inference, Energy, Vol.276, 2023, 127286.
Download Paper