no code implementations • 5 Jun 2023 • Lorenzo Nespoli, Vasco Medici
In this paper, we propose a general and practical approach to estimate the amount of flexibility of deferrable loads in a Distribution System Operator's (DSO) grid and obtain an optimal control policy from day zero, without relying on historical observations.
no code implementations • 14 Oct 2022 • Lorenzo Nespoli, Nina Wiedemann, Esra Suel, Yanan Xin, Martin Raubal, Vasco Medici
Deploying real-time control on large-scale fleets of electric vehicles (EVs) is becoming pivotal as the share of EVs over internal combustion engine vehicles increases.
no code implementations • 14 Oct 2020 • Dario Marvin, Lorenzo Nespoli, Davide Strepparava, Vasco Medici
The ability to forecast the concentration of air pollutants in an urban region is crucial for decision-makers wishing to reduce the impact of pollution on public health through active measures (e. g. temporary traffic closures).
2 code implementations • 8 Mar 2020 • Lorenzo Nespoli, Vasco Medici
We show that multivariate trees can outperform their univariate counterpart when the predictions are correlated.
no code implementations • 3 Oct 2019 • Lorenzo Nespoli, Vasco Medici, Kristijan Lopatichki, Fabrizio Sossan
We present a comparative study of different probabilistic forecasting techniques on the task of predicting the electrical load of secondary substations and cabinets located in a low voltage distribution grid, as well as their aggregated power profile.
1 code implementation • 21 Jun 2017 • Lorenzo Nespoli, Vasco Medici
Results from two case studies located in Switzerland are presented.