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Found 4 papers, 1 papers with code
Quantifying Non-linear Dependencies in Blind Source Separation of Power System Signals using Copula Statistics
This nonlinearity is a result of the intermittent nature of these resources and the switching behavior of their power electronic devices.
Identification of Power System Oscillation Modes using Blind Source Separation based on Copula Statistic
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.
Robust Gaussian Process Regression with Huber Likelihood
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.
A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow
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.
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