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07/26/2023
A Constraint Enforcement Deep Reinforcement Learning Framework for Optimal Energy Storage Systems Dispatch
The optimal dispatch of energy storage systems (ESSs) presents formidabl...
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03/20/2023
Targeted Analysis of High-Risk States Using an Oriented Variational Autoencoder
Variational autoencoder (VAE) neural networks can be trained to generate...
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09/08/2022
Generating Contextual Load Profiles Using a Conditional Variational Autoencoder
Generating power system states that have similar distribution and depend...
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08/01/2022
Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling
Taking advantage of their data-driven and model-free features, Deep Rein...
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10/21/2021
Generating Multivariate Load States Using a Conditional Variational Autoencoder
For planning of power systems and for the calibration of operational too...
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04/29/2020
Data-Assisted Model-Based Anomaly Detection for High-Fidelity Simulators of Power Systems
The main objective of this article is to develop scalable anomaly detect...
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03/04/2020
Detection of False Data Injection Attacks Using the Autoencoder Approach
The security of supply in a power grid critically depends on the ability...
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01/20/2020
False Data Injection Attacks on Hybrid AC/HVDC Interconnected System with Virtual Inertia – Vulnerability, Impact and Detection
Power systems are moving towards hybrid AC/DC grids with the integration...
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02/01/2019
Design of experiments aided holistic testing of cyber-physical energy systems
The complex and often safety-critical nature of cyber-physical energy sy...
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11/15/2018
Smart Grid Co-Simulation with MOSAIK and HLA: A Comparison Study
Evaluating new technological developments for energy systems is becoming...
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10/06/2017
