Participation analysis in impedance models: The grey-box approach for power system stability
This paper develops a grey-box approach to small-signal stability analysis of complex power
systems that facilitates root-cause tracing without requiring disclosure of the full details of the …
systems that facilitates root-cause tracing without requiring disclosure of the full details of the …
Information length quantification and forecasting of power systems kinetic energy
One of the short-coming challenges of power systems operation and planning is the difficulty
to quantify the variability of power systems Kinetic Energy (KE) to unveil online additional …
to quantify the variability of power systems Kinetic Energy (KE) to unveil online additional …
Data-driven stabilization of discrete-time control-affine nonlinear systems: A Koopman operator approach
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 being …
transfer operator techniques, namely, Perron-Frobenius and Koopman operators are being …
On quantification and maximization of information transfer in network dynamical systems
Abstract Information flow among nodes in a complex network describes the overall cause-
effect relationships among the nodes and provides a better understanding of the …
effect relationships among the nodes and provides a better understanding of the …
Causal analysis and classification of traffic crash injury severity using machine learning algorithms
Objectives Causal analysis and classification of injury severity applying non-parametric
methods for traffic crashes have received limited attention. This study presents a …
methods for traffic crashes have received limited attention. This study presents a …
Online real-time learning of dynamical systems from noisy streaming data
Recent advancements in sensing and communication facilitate obtaining high-frequency
real-time data from various physical systems like power networks, climate systems …
real-time data from various physical systems like power networks, climate systems …
Application of advanced causal analyses to identify processes governing secondary organic aerosols
Understanding how different physical and chemical atmospheric processes affect the
formation of fine particles has been a persistent challenge. Inferring causal relations …
formation of fine particles has been a persistent challenge. Inferring causal relations …
Data-driven operator theoretic methods for phase space learning and analysis
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 subsets in …
space of a dynamical system. We defined conditions for discovering new invariant subsets in …
[HTML][HTML] Study the impact of renewable and non-renewable energy sources on micro-grid using time series data based information transfer
This paper addresses the challenges arising from the integration of renewable energy
sources into microgrids, focusing on the impact on system dynamics and stability. Employing …
sources into microgrids, focusing on the impact on system dynamics and stability. Employing …
On few shot learning of dynamical systems: A koopman operator theoretic approach
In this paper, we propose a novel algorithm for learning the Koopman operator of a
dynamical system from a\textit {small} amount of training data. In many applications of data …
dynamical system from a\textit {small} amount of training data. In many applications of data …