| KEYWORD |
Residential energy demand forecasting
Parole chiave AGENT BASED SIMULATION, ENERGY CONSUMPTION FORECASTING, ICT, SMAR CITY, SIMULATION, SMART CITIES, SMART GRIDS, USER BEHAVIOUR
Riferimenti LORENZO BOTTACCIOLI, EDOARDO PATTI
Riferimenti esterni Claudia De Vizia (claudia.devizia@polito.it)
Gruppi di ricerca DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ELECTRONIC DESIGN AUTOMATION - EDA, Energy Center Lab, GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ICT4SS - ICT FOR SMART SOCIETIES
Tipo tesi SPERIMENTALE
Descrizione Energy demand forecasting is needed for the correct operation and the optimisation of the power system since it allows to plan activities such as energy resources management and storage. Various methods have been analysed for energy demand forecasting (Kalman Filter, regressive analysis and Artificial Neural Network,..), but there is always a need to improve the prediction.
Moreover, the growth in electricity consumption over the last decade is due to the residential and services sectors. Thus, residential energy demand forecasting is taking on an increasingly important role and ad-hoc methods may be considered.
This thesis aims at improving the household load forecasting comparing different methods and taking into account different parameters.
Indeed, household energy consumption is strictly related to the user’s habit. Thus, including users’ behaviour and users’ preference parameters would increase the accuracy of the load forecasting.
Scadenza validita proposta 07/08/2025
PROPONI LA TUA CANDIDATURA