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Found 5 papers, 1 papers with code
Modeling and Detection of Future Cyber-Enabled DSM Data Attacks using Supervised Learning
In future smart grids, certain portions of a customers load usage could be under automatic control with a cyber-enabled DSM program which selectively schedules loads as a function of electricity prices to improve power balance and grid stability.
A Novel Smoothed Loss and Penalty Function for Noncrossing Composite Quantile Estimation via Deep Neural Networks
However, one major shortcoming of composite quantile estimation in neural networks is the quantile crossover problem.
An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power
Uncertainty analysis in the form of probabilistic forecasting can provide significant improvements in decision-making processes in the smart power grid for better integrating renewable energies such as wind.
A Composite Quantile Fourier Neural Network for Multi-Step Probabilistic Forecasting of Nonstationary Univariate Time Series
We present a novel quantile Fourier neural network is for nonparametric probabilistic forecasting of univariate time series.
Smooth Pinball Neural Network for Probabilistic Forecasting of Wind Power
Multiple quantiles are estimated to form 10%, to 90% prediction intervals which are evaluated using a quantile score and reliability measures.
