Search Results for author: Lamine Mili

Found 12 papers, 1 papers with code

Voltage-Dependent Electromechanical Wave Propagation Modeling for Dynamic Stability Analysis in Power Systems

no code implementations21 Nov 2023 Somayeh Yarahmadi, Daniel Adrian Maldonado, Lamine Mili, Junbo Zhao, Mihai Anitescu

Analyzing these characteristics enables the assessment of the impacts of EMW on the performance of the protection system.

Quantifying Non-linear Dependencies in Blind Source Separation of Power System Signals using Copula Statistics

no code implementations14 Sep 2023 Pooja Algikar, Lamine Mili, Kiran Karra, Akash Algikar, Mohsen Ben Hassine

This nonlinearity is a result of the intermittent nature of these resources and the switching behavior of their power electronic devices.

blind source separation

Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model

no code implementations31 Mar 2023 Yijun Xu, Marcos Netto, Lamine Mili

We propose a Koopman operator-based surrogate model for propagating parameter uncertainties in power system nonlinear dynamic simulations.

Computational Efficiency

Identification of Power System Oscillation Modes using Blind Source Separation based on Copula Statistic

1 code implementation7 Feb 2023 Pooja Algikar, Lamine Mili, Mohsen Ben Hassine, Somayeh Yarahmadi, Almuatazbellah, Boker

We access the performance of the proposed method on numerical simulation signals and recorded data from a simulation of time domain analysis on the classical 11-Bus 4-Machine test system.

blind source separation

Robust Gaussian Process Regression with Huber Likelihood

no code implementations19 Jan 2023 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 distribution using Gaussian conditioning.

Bayesian Inference regression

A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow

no code implementations6 Jan 2023 Pooja Algikar, Yijun Xu, Somayeh Yarahmadi, Lamine Mili

The proposed method is demonstrated on the IEEE 33-Bus power distribution system and a real-world unbalanced 240-bus power distribution system heavily integrated with renewable energy sources.

Time Series Time Series Analysis

An Adaptive-Importance-Sampling-Enhanced Bayesian Approach for Topology Estimation in an Unbalanced Power Distribution System

no code implementations18 Oct 2021 Yijun Xu, Jaber Valinejad, Mert Korkali, Lamine Mili, Yajun Wang, Xiao Chen, Zongsheng Zheng

To overcome the above challenges, this paper proposes a Bayesian-inference framework that allows us to simultaneously estimate the topology and the state of a three-phase, unbalanced power distribution system.

Bayesian Inference

Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs

no code implementations31 May 2021 Marcos Netto, Venkat Krishnan, Yingchen Zhang, Lamine Mili

For instance, the advent of new technologies in sensing and measurement, as well as in communications and networking, might impact the cost and performance of available solutions and shift initially set conditions.

A robust extended Kalman filter for power system dynamic state estimation using PMU measurements

no code implementations5 Apr 2021 Marcos Netto, Junbo Zhao, Lamine Mili

Simulations carried out on the IEEE 39-bus test system reveal that our robust extended Kalman filter exhibits good tracking capabilities under Gaussian process and observation noise while suppressing observation outliers, even in position of leverage.

On the Effect of Suboptimal Estimation of Mutual Information in Feature Selection and Classification

no code implementations30 Apr 2018 Kiran Karra, Lamine Mili

This paper introduces a new property of estimators of the strength of statistical association, which helps characterize how well an estimator will perform in scenarios where dependencies between continuous and discrete random variables need to be rank ordered.

feature selection General Classification

Copula Index for Detecting Dependence and Monotonicity between Stochastic Signals

no code implementations20 Mar 2017 Kiran Karra, Lamine Mili

This paper introduces a nonparametric copula-based index for detecting the strength and monotonicity structure of linear and nonlinear statistical dependence between pairs of random variables or stochastic signals.

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