| KEYWORD |
Characterization of occupant behaviour in buildings through data analytics techniques
keywords BUILDING ENERGY MANAGEMENT, DATA ANALYTICS, ENERGY INFORMATION SYSTEMS, INTELLIGENT BUILDINGS
Reference persons ALFONSO CAPOZZOLI
Research Groups BAEDA lab (www.baeda.polito.it), TEBE
Description Occupant behaviour is one of the major factors influencing building energy consumption and introducing sources of uncertainty in building energy use prediction and simulation. Currently the exploitation and characterization of occupant-related data in buildings is insufficient thus limiting opportunities of building design optimizations and energy management improvements. Occupant behaviour is associated with various actions that have a direct or indirect impact upon building energy consumption such as adjustment of thermostat settings, opening and closing of windows, dimming and switching of lights, use of blinds, turning on/off of HVAC systems, presence and movement in building spaces. Quantifying the effect of occupant behaviour on building energy consumption and the potential energy saving achievable through its modification remain primary challenges.
In this perspective the thesis project aims at defining a systematic approach for the analysis of occupant-related data that can support the robust identification of typical and infrequent behaviours of occupants in buildings.
Deadline 24/02/2023
PROPONI LA TUA CANDIDATURA