10 citations · 10 across the 6 of their papers we have counts for
8 papers
Sensor-Aware Joint Data Fusion and State Estimation under Sparse Multi-rate Distribution Grid Sensing
Pooja Algikar, Stefano Fenu, Kumarsinh Jhala +1
Distribution-system state estimation is a growing necessity for the modern power grid as the addition of local storage and generation add system complexity that an operator or aggr…
Double-arc rearrangement and the symmetric isoperimetric problem in Gauss space
Marco Barchiesi, Filippo Cagnetti, Vesa Julin
We provide a new rearrangement in Gauss space transforming symmetric sets while decreasing their Gaussian perimeter. We use this rearrangement to analyze the minimizers of the Gaus…
Statistical analysis and method to quantify the impact of measurement uncertainty on dynamic mode decomposition
P. Algikar, P. Sharma, M. Netto +1
We apply random matrix theory to study the impact of measurement uncertainty on dynamic mode decomposition. Specifically, when the measurements follow a normal probability density…
Quantifying Non-linear Dependencies in Blind Source Separation of Power System Signals using Copula Statistics
Pooja Algikar, Lamine Mili, Kiran Karra +2
The dynamics of a power system with a significant presence of renewable energy resources are growing increasingly nonlinear. This nonlinearity is a result of the intermittent natur…
Identification of Power System Oscillation Modes using Blind Source Separation based on Copula Statistic
Pooja Algikar, Lamine Mili, Mohsen Ben Hassine +3
The dynamics of a power system with large penetration of renewable energy resources are becoming more nonlinear due to the intermittence of these resources and the switching of the…
Robust Gaussian Process Regression with Huber Likelihood
Pooja Algikar, Lamine Mili
Gaussian process regression in its most simplified form assumes normal homoscedastic noise and utilizes analytically tractable mean and covariance functions of predictive posterior…
A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow
Pooja Algikar, Yijun Xu, Somayeh Yarahmadi +1
In this paper, we propose a robust data-driven process model whose hyperparameters are robustly estimated using the Schweppe-type generalized maximum likelihood estimator. The prop…
A Measurement-Based Robust Non-Gaussian Process Emulator Applied to Data-Driven Stochastic Power Flow
Pooja Algikar, Yijun Xu, Lamine Mili
In this paper, we propose a robust non-Gaussian process emulator based on the Schweppe-type generalized maximum likelihood estimator, which is trained on metered time series of vol…