activity
20202023
most citedDemand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process

90 citations · 103 across the 7 of their papers we have counts for

collaborators

7 papers

math.OC2023★ 7 cited

An optimal hierarchical control scheme for smart generation units: an application to combined steam and electricity generation

Stefano Spinelli, Marcello Farina, Andrea Ballarino

Optimal management of thermal and energy grids with fluctuating demand and prices requires to orchestrate the generation units (GU) among all their operating modes. A hierarchical…

eess.SY2023★ 4 cited

A Hierarchical Architecture for Optimal Unit Commitment and Control of an Ensemble of Steam Generators

Stefano Spinelli, Marcello Farina, Andrea Ballarino

A hierarchical architecture for the optimal management of an ensemble of steam generators is presented. The subsystems are coordinated by a multilayer scheme for jointly sustaining…

math.OC2023★ 90 cited

Demand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process

Danial Ramin, Stefano Spinelli, Alessandro Brusaferri

The increasing challenges to the grid stability posed by the penetration of renewable energy resources urge a more active role for demand response programs as viable alternatives t…

eess.SP2021

Probabilistic electric load forecasting through Bayesian Mixture Density Networks

Alessandro Brusaferri, Matteo Matteucci, Stefano Spinelli +1

Probabilistic load forecasting (PLF) is a key component in the extended tool-chain required for efficient management of smart energy grids. Neural networks are widely considered to…

cs.LG2020★ 2 cited

Estimation of Switched Markov Polynomial NARX models

Alessandro Brusaferri, Matteo Matteucci, Stefano Spinelli

This work targets the identification of a class of models for hybrid dynamical systems characterized by nonlinear autoregressive exogenous (NARX) components, with finite-dimensiona…

cs.LG2020

Identification of Probability weighted ARX models with arbitrary domains

Alessandro Brusaferri, Matteo Matteucci, Stefano Spinelli

Hybrid system identification is a key tool to achieve reliable models of Cyber-Physical Systems from data. PieceWise Affine models guarantees universal approximation, local lineari…