Abstract
Measuring and identifying human behaviours are key aspects to support the simulation processes that have a significant role in buildings’ (and cities’) design and management. In fact, layout assessments and control strategies are deeply influenced by the prediction of building performance. However, the missing inclusion of the human component within the building-related processes leads to large discrepancies between actual and simulated outcomes. This paper presents a methodology for measuring specific human behaviours in buildings and developing human-in-the-loop design applied to retrofit and renovation interventions. The framework concerns the detailed building monitoring and the development of stochastic and data-driven behavioural models and their coupling within energy simulation software using a cosimulation approach. The methodology has been applied to a real case study to illustrate its applicability. A one-year monitoring has been carried out through a dedicated sensor network for the data recording and to identify the triggers of users’ actions. Then, two stochastic behavioural models (i.e., one for predicting light switching and one for window opening) have been developed (using the measured data) and coupled within the IESVE simulation software. A simplified energy model of the case study has been created to test the behavioural approach. The outcomes highlight that the behavioural approach provides more accurate results than a standard one when compared to real profiles. The adoption of behavioural profiles leads to a reduction of the discrepancy with respect to real profiles up to 58% and 26% when simulating light switching and ventilation, respectively, in comparison to standard profiles. Using data-driven techniques to include the human component in the simulation processes would lead to better predictions both in terms of energy use and occupants’ comfort sensations. These aspects can be also included in building control processes (e.g., building management systems) to enhance the environmental and system management.
Highlights
Occupants are the key factor for the building energy assessment [1] since they influence the indoor environment both in a passive and active way [2]
This paper presents a methodology for the human-in-theloop design applied to building retrofit and renovation. It started from the target of measuring, fitting, and including the behavioural component in the simulation environment to enhance the predictions of building performance
A one-year monitoring in a demo site allowed the development of data-driven behavioural models to predict lightswitching and window-opening behaviours in offices
Summary
Occupants are the key factor for the building energy assessment [1] since they influence the indoor environment both in a passive and active way [2]. The former is related to the presence of the users just in terms of sources of heat and CO2 production. Allowing data exchange between different modules in real time, this approach accurately reproduces the mutual interactions and influences between the occupants and the environment. The literature analysis provides a clear evidence of the advantages derived from cosimulation approach applied to building performance assessment. There is the need to increase the knowledge on how behaviours can be accurately measured and fitted for wider application in the context of building design and management
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