33 citations · 63 across the 13 of their papers we have counts for
15 papers
AI-based Identification of Most Critical Cyberattacks in Industrial Systems
Bruno Paes Leao, Jagannadh Vempati, Siddharth Bhela +2
Modern industrial systems face a growing threat from sophisticated cyberattacks that can cause significant operational disruptions. This work presents a novel methodology for ident…
Constrained Reinforcement Learning for Predictive Control in Real-Time Stochastic Dynamic Optimal Power Flow
Tong Wu, Anna Scaglione, Daniel Arnold
Deep Reinforcement Learning (DRL) has become a popular method for solving control problems in power systems. Conventional DRL encourages the agent to explore various policies encod…
Complex-Value Spatio-temporal Graph Convolutional Neural Networks and its Applications to Electric Power Systems AI
Tong Wu, Anna Scaglione, Daniel Arnold
The effective representation, precessing, analysis, and visualization of large-scale structured data over graphs are gaining a lot of attention. So far most of the literature has f…
Spatio-Temporal Graph Convolutional Neural Networks for Physics-Aware Grid Learning Algorithms
Tong Wu, Ignacio Losada Carreno, Anna Scaglione +1
This paper proposes a model-free Volt-VAR control (VVC) algorithm via the spatio-temporal graph ConvNet-based deep reinforcement learning (STGCN-DRL) framework, whose goal is to co…
Adaptive Control of Distributed Energy Resources for Distribution Grid Voltage Stability
Daniel Arnold, Shammya Saha, Sy-Toan Ngo +5
Volt-VAR and Volt-Watt functionality in photovoltaic (PV) smart inverters provide mechanisms to ensure system voltage magnitudes and power factors remain within acceptable limits.…
Adam-based Augmented Random Search for Control Policies for Distributed Energy Resource Cyber Attack Mitigation
Daniel Arnold, Sy-Toan Ngo, Ciaran Roberts +3
Volt-VAR and Volt-Watt control functions are mechanisms that are included in distributed energy resource (DER) power electronic inverters to mitigate excessively high or low voltag…