3 citations · 8 across the 26 of their papers we have counts for
29 papers
Managing Risks from Large Digital Loads Using Coordinated Grid-Forming Storage Network
Soumya Kundu, Kaustav Chatterjee, Ramij R. Hossain +2
Anticipated rapid growth of large digital load, driven by artificial intelligence (AI) data centers, is poised to increase uncertainty and large fluctuations in consumption, threat…
Advancing Cyber-Attack Detection in Power Systems: A Comparative Study of Machine Learning and Graph Neural Network Approaches
Tianzhixi Yin, Syed Ahsan Raza Naqvi, Sai Pushpak Nandanoori +1
This paper explores the detection and localization of cyber-attacks on time-series measurements data in power systems, focusing on comparing conventional machine learning (ML) like…
Empowering the Grid: Decentralized Autonomous Control for Effective Utilization and Resilience
Sai Pushpak Nandanoori, Alok Kumar Bharati, Subhrajit Sinha +3
With the emergence of low-inertia microgrids powered by inverter-based generation, there remains a concern about the operational resilience of these systems. Grid-forming inverters…
Frequency Control and Disturbance Containment Using Grid-Forming Embedded Storage Networks
Kaustav Chatterjee, Ramij Raja Hossain, Sai Pushpak Nandanoori +3
The paper discusses fast frequency control in bulk power systems using embedded networks of grid-forming energy storage resources. Differing from their traditional roles of regulat…
Coordinated Frequency Regulation in Grid-Forming Storage Network via Safety-Consensus
Ramij Raja Hossain, Kaustav Chatterjee, Sai Pushpak Nandanoori +4
Inverter-based storages are poised to play a prominent role in future power grids with massive renewable generation. Grid-forming inverters (GFMs) are emerging as a dominant techno…
Grid-Forming Storage Networks: Analytical Characterization of Damping and Design Insights
Kaustav Chatterjee, Ramij Raja Hossain, Sai Pushpak Nandanoori +4
The paper presents a theoretical study on small-signal stability and damping in bulk power systems with multiple grid-forming inverter-based storage resources. A detailed analysis…
Isolating Signatures of Cyberattacks under Stressed Grid Conditions
Sanchita Ghosh, Syed Ahsan Raza Naqvi, Sai Pushpak Nandanoori +1
In a controlled cyber-physical network, such as a power grid, any malicious data injection in the sensor measurements can lead to widespread impact due to the actions of the closed…
Losing Control of your Network? Try Resilience Theory
Jean-Baptiste Bouvier, Sai Pushpak Nandanoori, Melkior Ornik
Resilience of cyber-physical networks to unexpected failures is a critical need widely recognized across domains. For instance, power grids, telecommunication networks, transportat…
Online Real-time Learning of Dynamical Systems from Noisy Streaming Data: A Koopman Operator Approach
S. Sinha, Sai P. Nandanoori, David Barajas-Solano
Recent advancements in sensing and communication facilitate obtaining high-frequency real-time data from various physical systems like power networks, climate systems, biological n…
Data-driven Stabilization of Discrete-time Control-affine Nonlinear Systems: A Koopman Operator Approach
Subhrajit Sinha, Sai Pushpak Nandanoori, Jan Drgona +1
In recent years data-driven analysis of dynamical systems has attracted a lot of attention and transfer operator techniques, namely, Perron-Frobenius and Koopman operators are bein…
Distributed Transient Safety Verification via Robust Control Invariant Sets: A Microgrid Application
Jean-Baptiste Bouvier, Sai Pushpak Nandanoori, Melkior Ornik +1
Modern safety-critical energy infrastructures are increasingly operated in a hierarchical and modular control framework which allows for limited data exchange between the modules.…
Graph Neural Network and Koopman Models for Learning Networked Dynamics: A Comparative Study on Power Grid Transients Prediction
Sai Pushpak Nandanoori, Sheng Guan, Soumya Kundu +4
Continuous monitoring of the spatio-temporal dynamic behavior of critical infrastructure networks, such as the power systems, is a challenging but important task. In particular, ac…
Data-Driven Operator Theoretic Methods for Phase Space Learning and Analysis
Sai Pushpak Nandanoori, Subhrajit Sinha, Enoch Yeung
This paper uses data-driven operator theoretic approaches to explore the global phase space of a dynamical system. We defined conditions for discovering new invariant subspaces in…
Sparse Control Synthesis for Uncertain Responsive Loads with Stochastic Stability Guarantees
Sai Pushpak Nandanoori, Soumya Kundu, Jianming Lian +3
Recent studies have demonstrated the potential of flexible loads in providing frequency response services. However, uncertainty and variability in various weather-related and end-u…
Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes
Sai Pushpak Nandanoori, Soumya Kundu, Seemita Pal +2
Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disrup…
Computationally Efficient Learning of Large Scale Dynamical Systems: A Koopman Theoretic Approach
Subhrajit Sinha, Sai Pushpak Nandanoori, Enoch Yeung
In recent years there has been a considerable drive towards data-driven analysis, discovery and control of dynamical systems. To this end, operator theoretic methods, namely, Koopm…
Stochastic Virtual Battery Modeling of Uncertain Electrical Loads Using Variational Autoencoder
Indrasis Chakraborty, Sai Pushpak Nandanoori, Soumya Kundu +1
Effective utilization of flexible loads for grid services, while satisfying end-user preferences and constraints, requires an accurate estimation of the aggregated predictive flexi…
Distributed Small-Signal Stability Conditions for Inverter-Based Unbalanced Microgrids
Sai Pushpak Nandanoori, Soumya Kundu, Wei Du +2
The proliferation of inverter-based generation and advanced sensing, controls, and communication infrastructure have facilitated the accelerated deployment of microgrids. A coordin…
Data Driven Online Learning of Power System Dynamics
Subhrajit Sinha, Sai Pushpak Nandanoori, Enoch Yeung
With the advancement of sensing and communication in power networks, high-frequency real-time data from a power network can be used as a resource to develop better monitoring capab…
Koopman Operator Methods for Global Phase Space Exploration of Equivariant Dynamical Systems
Subhrajit Sinha, Sai P. Nandanoori, Enoch Yeung
In this paper, we develop the Koopman operator theory for dynamical systems with symmetry. In particular, we investigate how the Koopman operator and eigenfunctions behave under th…
Data-Driven Operator Theoretic Methods for Global Phase Space Learning
Sai Pushpak Nandanoori, Subhrajit Sinha, Enoch Yeung
In this work, we propose to apply the recently developed Koopman operator techniques to explore the global phase space of a nonlinear system from time-series data. In particular, w…
Online Learning of Dynamical Systems: An Operator Theoretic Approach
Subhrajit Sinha, Sai Pushpak Nandanoori, Enoch Yeung
In this paper, we provide an algorithm for online computation of Koopman operator in real-time using streaming data. In recent years, there has been an increased interest in data-d…
Distribution System State Estimation in the Presence of High Solar Penetration
Thiagarajan Ramachandran, Andrew Reiman, Sai Pushpak Nandanoori +2
Low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communicati…
Distributed Barrier Certificates for Safe Operation of Inverter-Based Microgrids
Soumya Kundu, Sijia Geng, Sai Pushpak Nandanoori +2
Inverter-interfaced microgrids differ from the traditional power systems due to their lack of inertia. Vanishing timescale separation between voltage and frequency dynamics makes i…