Occupants' behavior exerts a significant influence on the energy performance of residential buildings. Industrial energy simulation tools often account for occupants' as monolithic elements with standard averaged energy consumption profiles. Predictions yielded by these tools can thus deviate dramatically from reality. This paper proposes an activity-based model for forecasting energy and water consumption of households and discusses how such an occupant-focused model may integrate a user-focused design of residential buildings. A literature review is first presented followed by a brief recall of the proposed modeling methodology and a sample of simulation results. The possible integration of the proposed model into the design and energy management processes of residential buildings is then demonstrated through a number of use cases.

Building occupants are considered as a major source of uncertainty in energy modeling nowadays. Yet, industrial energy simulation tools often account for occupant behavior through some predefined scenarios and fixed consumption profiles which yield to unrealistic and inaccurate predictions. In this paper, a stochastic activity-based approach for forecasting occupant-related energy consumption in residential buildings is proposed. First, the model is exposed together with its different variables. Second, a direct application of the model on the domestic activity “washing laundry” is performed. A number of simulations are performed and their results are presented and discussed. Finally, the model is validated by confronting simulation results to real measured data.

Residents' usages and behavior play a determining role in the variability of the energy consumption and environmental impact of residential buildings during their use-phase. At present, however, they are inadequately documented and understood, as well as being highly variable. In this paper, we propose a use-phase memory model for residential buildings, whose aim is to store energy consumption and usage patterns. This storage can be done automatically or voluntarily. We give examples of useful information extracted from the data captured. The objective of this data analysis and synthesis is to provide building experts two specific use-cases: designing a new sustainable building, and renovating an existing one. Our model is deployed on a residential building, integrating the beneficial services for all stakeholders to demonstrate a sustainable relationship between designers, the residential building and the users. KeywordsUse-phase memory, environmental impact, user behavior, built environment, design tools