48 citations · 333 across the 22 of their papers we have counts for
25 papers
Equal CER, Unequal Damage: Severity-Weighted Character Error Rate for OCR
Nguyen Nguyen, Yongyi Zang
Character Error Rate (CER), the standard metric for OCR and vision-language models (VLMs), charges a typo as much as a wrong name. We introduce semCER, which keeps CER's alignment…
Fast Analytical Method for Resource Adequacy Assessment in Renewable-Rich Power Systems
Seyed Amir Hosseini, Mohammad Reza Karimi Gharigh, Antonello Monti +2
This paper proposes a novel analytical method for resource adequacy assessment in renewable rich power systems. The approach begins by applying the stress strength method to estima…
Towards Scalable FMI-based Co-simulation of Wind Energy Systems Using PowerFactory
Arjen A van der Meer, Rishabh Bhandia, Edmund Widl +5
Due to the increased deployment of renewable energy sources and intelligent components the electric power system will exhibit a large degree of heterogeneity, which requires inclus…
A Constraint Enforcement Deep Reinforcement Learning Framework for Optimal Energy Storage Systems Dispatch
Shengren Hou, Edgar Mauricio Salazar Duque, Peter Palensky +1
The optimal dispatch of energy storage systems (ESSs) presents formidable challenges due to the uncertainty introduced by fluctuations in dynamic prices, demand consumption, and re…
Impact of Dynamic Tariffs for Smart EV Charging on LV Distribution Network Operation
Flore Verbist, Nanda Kishor Panda, Pedro P. Vergara +1
With a growing share of electric vehicles (EVs) in our distribution grids, the need for smart charging becomes indispensable to minimise grid reinforcement. To circumvent the assoc…
Optimal Energy System Scheduling Using A Constraint-Aware Reinforcement Learning Algorithm
Hou Shengren, Pedro P. Vergara, Edgar Mauricio Salazar Duque +1
The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system's complexity, especially when it comes to defining its operati…
Targeted Analysis of High-Risk States Using an Oriented Variational Autoencoder
Chenguang Wang, Ensieh Sharifnia, Simon H. Tindemans +1
Variational autoencoder (VAE) neural networks can be trained to generate power system states that capture both marginal distribution and multivariate dependencies of historical dat…
Generating Contextual Load Profiles Using a Conditional Variational Autoencoder
Chenguang Wang, Simon H. Tindemans, Peter Palensky
Generating power system states that have similar distribution and dependency to the historical ones is essential for the tasks of system planning and security assessment, especiall…
Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling
Hou Shengren, Edgar Mauricio Salazar, Pedro P. Vergara +1
Taking advantage of their data-driven and model-free features, Deep Reinforcement Learning (DRL) algorithms have the potential to deal with the increasing level of uncertainty due…
Generating Multivariate Load States Using a Conditional Variational Autoencoder
Chenguang Wang, Ensieh Sharifnia, Zhi Gao +2
For planning of power systems and for the calibration of operational tools, it is essential to analyse system performance in a large range of representative scenarios. When the ava…
Training Strategies for Autoencoder-based Detection of False Data Injection Attacks
Chenguang Wang, Kaikai Pan, Simon Tindemans +1
The security of energy supply in a power grid critically depends on the ability to accurately estimate the state of the system. However, manipulated power flow measurements can pot…
Dynamic Anomaly Detection with High-fidelity Simulators: A Convex Optimization Approach
Kaikai Pan, Peter Palensky, Peyman Mohajerin Esfahani
The main objective of this article is to develop scalable dynamic anomaly detectors when high-fidelity simulators of power systems are at our disposal. On the one hand, mathematica…
Detection of False Data Injection Attacks Using the Autoencoder Approach
Chenguang Wang, Simon Tindemans, Kaikai Pan +1
State estimation is of considerable significance for the power system operation and control. However, well-designed false data injection attacks can utilize blind spots in conventi…
False Data Injection Attacks on Hybrid AC/HVDC Interconnected System with Virtual Inertia -- Vulnerability, Impact and Detection
Kaikai Pan, Elyas Rakhshani, Peter Palensky
Power systems are moving towards hybrid AC/DC grids with the integration of HVDC links, renewable resources and energy storage modules. New models of frequency control have to cons…
From Static to Dynamic Anomaly Detection with Application to Power System Cyber Security
Kaikai Pan, Peter Palensky, Peyman Mohajerin Esfahani
Developing advanced diagnosis tools to detect cyber attacks is the key to security of power systems. It has been shown that multivariate data injection attacks can bypass bad data…
Design of experiments aided holistic testing of cyber-physical energy systems
Arjen van der Meer, Cornelius Steinbrink, Kai Heussen +6
The complex and often safety-critical nature of cyber-physical energy systems makes validation a key challenge in facilitating the energy transition, especially when it comes to th…
Smart Grid Co-Simulation with MOSAIK and HLA: A Comparison Study
Cornelius Steinbrink, Arjen A. van der Meer, Milos Cvetkovic +4
Evaluating new technological developments for energy systems is becoming more and more complex. The overall application environment is a continuously growing and interconnected cyb…
Validating Intelligent Power and Energy Systems - A Discussion of Educational Needs
Panos Kotsampopoulos, Nikos Hatziargyriou, Thomas I. Strasser +13
Traditional power systems education and training is flanked by the demand for coping with the rising complexity of energy systems, like the integration of renewable and distributed…
Simulation-based Validation of Smart Grids - Status Quo and Future Research Trends
Cornelius Steinbrink, Sebastian Lehnhoff, Sebastian Rohjans +22
Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communicatio…
An Integrated Research Infrastructure for Validating Cyber-Physical Energy Systems
Thomas I. Strasser, Cyndi Moyo, Roland Bründlinger +22
Renewables are key enablers in the plight to reduce greenhouse gas emissions and cope with anthropogenic global warming. The intermittent nature and limited storage capabilities of…
Data Attacks on Power System State Estimation: Limited Adversarial Knowledge vs. Limited Attack Resources
Kaikai Pan, André Teixeira, Milos Cvetkovic +1
A class of data integrity attack, known as false data injection (FDI) attack, has been studied with a considerable amount of work. It has shown that with perfect knowledge of the s…
Cyber Risk Analysis of Combined Data Attacks Against Power System State Estimation
Kaikai Pan, André Teixeira, Milos Cvetkovic +1
Understanding smart grid cyber attacks is key for developing appropriate protection and recovery measures. Advanced attacks pursue maximized impact at minimized costs and detectabi…
Co-simulation for Cyber Security Analysis: Data Attacks against Energy Management System
Kaikai Pan, André Teixeira, Claudio López +1
It is challenging to assess the vulnerability of a cyber-physical power system to data attacks from an integral perspective. In order to support vulnerability assessment except ana…
Cyber-Physical Energy Systems Modeling, Test Specification, and Co-Simulation Based Testing
Arjen A. van der Meer, Peter Palensky, Kai Heussen +15
The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. E…