Emilie Chapotot

An Occupant-Based Energy Consumption Model for User-Focused Design of Residential Buildings

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.

AN EXPERIMENTAL APPROACH TO ASSESS THE DISPARITIES IN THE USAGE TRENDS OF DOMESTIC ELECTRIC LIGHTING

In a country like France, electricity consumption d evoted to domestic lighting represents nearly a fifth of the total energy consumption of a building. The use of electric ligh ting is influenced by several factors such as the building’ s structural characteristics, the activities of its occupants, tlighting equipments, and the level of natural light. Designe rs do take into account, in their energy models, the influence of occupants on the building’s overall energy consumption. Howev er, these models still have some drawbacks regarding the comp rehension of real “occupants’ energy behaviors” which play an important role in the discrepancies between predicted and rea l energy consumptions. The behavioral factors behind occupan ts’ usage trends of energy are still not thoroughly explored. Therefore, it is assumed that a better comprehension of these beh aviors and consumption mechanisms could lead to the identifica tion of technical solutions and energy saving potentials, tresulting in a more robust building design. The present paper aims to provide an insight into domestic lighting usages. The main objective is to explore t he key factors (socio-demographic, economic, technical and behavio ral) responsible for the disparities in lighting consump tion between one household and another. For this purpose, an exp eriment is performed concurrently to the proposal of a lightin g usage model. A micro level investigation protocol is elab orated and used to conduct in-depth studies on the usage patte rns of electric lighting. The survey is conducted on a sam ple of 8 French households. The methodology for constructing the experimental protocol, its deployment, as well as t he results obtained and their analysis are presented in this p aper. The need for further qualitative and quantitative studi es to better understand the usage trends of electric lighting is discussed.

A Stochastic Activity-Based Approach for Forecasting Occupant-Related Energy Consumption in Residential Buildings

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.Copyright

FOR A SUSTAINABLE DIALOGUE: THE GREEN-USE (GU) LEARNING CYCLES CONCEPT

Product design is now driven to the satisfaction of requirements all along the life cycle of the product, with an increased concern in environmental impact. A new concept, the Green-Use (GU) Learning Cycles, is proposed. It is used to determine the way a continuous, adaptive interaction between user and product can be established to improve environmental performance during use. It is structured by two levels of analysis (macro and micro) and a cyclic nature. These levels are the ”Incremental user involvement levels”, and the ”Environmental Impact in Use”. They are modelled around the notion of an evolution in cycles, from the initial state of the system product-user to a final stage which results in optimal use with minimal environmental impact. This work includes experimentation to support the new concept proposed, as well a method to use it.