4 citations · 11 across the 5 of their papers we have counts for
5 papers
Bayesian Error-in-Variables Models for the Identification of Power Networks
Jean-Sébastien Brouillon, Emanuele Fabbiani, Pulkit Nahata +3
The increasing integration of intermittent renewable generation, especially at the distribution level,necessitates advanced planning and optimisation methodologies contingent on th…
Identification of AC Networks via Online Learning
Emanuele Fabbiani, Pulkit Nahata, Giuseppe De Nicolao +1
The increasing penetration of intermittent distributed energy resources in power networks calls for novel planning and control methodologies which hinge on detailed knowledge of th…
Ensembling methods for countrywide short term forecasting of gas demand
Emanuele Fabbiani, Andrea Marziali, Giuseppe De Nicolao
Gas demand is made of three components: Residential, Industrial, and Thermoelectric Gas Demand. Herein, the one-day-ahead prediction of each component is studied, using Italian dat…
Forecasting residential gas demand: machine learning approaches and seasonal role of temperature forecasts
Andrea Marziali, Emanuele Fabbiani, Giuseppe De Nicolao
Gas demand forecasting is a critical task for energy providers as it impacts on pipe reservation and stock planning. In this paper, the one-day-ahead forecasting of residential gas…
Fast calibration of two-factor models for energy option pricing
Emanuele Fabbiani, Andrea Marziali, Giuseppe De Nicolao
Energy companies need efficient procedures to perform market calibration of stochastic models for commodities. If the Black framework is chosen for option pricing, the bottleneck o…