no code implementations • 27 Sep 2019 • Kostas Hatalis, Parv Venkitasubramaniam, Shalinee Kishore
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.
no code implementations • 24 Sep 2019 • Kostas Hatalis, Alberto J. Lamadrid, Katya Scheinberg, Shalinee Kishore
However, one major shortcoming of composite quantile estimation in neural networks is the quantile crossover problem.
no code implementations • 29 Mar 2018 • Kostas Hatalis, Shalinee Kishore, Katya Scheinberg, Alberto Lamadrid
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.
no code implementations • 27 Dec 2017 • Kostas Hatalis, Shalinee Kishore
We present a novel quantile Fourier neural network is for nonparametric probabilistic forecasting of univariate time series.
1 code implementation • 4 Oct 2017 • Kostas Hatalis, Alberto J. Lamadrid, Katya Scheinberg, Shalinee Kishore
Multiple quantiles are estimated to form 10%, to 90% prediction intervals which are evaluated using a quantile score and reliability measures.