The objective of this article is to provide a methodology for optimizing the envelope of a building with respect to the triple objective of heating load, cooling load and daylight. The variables to optimize are the window to wall area ratio (WWR) and the window type characterized by its visual and thermal characteristics (visual and solar transmittance, and U-value). Energy load is computed using building performance simulation software (TRNSYS). A criterion of daylight is defined as the integrated time when the illuminance is below a threshold and artificial light is required. This criterion was calculated using the software Daysim. The variables have antagonistic effects on the objectives: WWR and window type may have opposite effects by increasing solar gain and daylight duration during winter, which would be beneficial, but could lead to overheating during summer. Therefore, an easy-to-set up methodology is proposed to find the optimal solutions of such a problem. A multi-objective optimization was performed in order to find the optimal variables leading to the minimization of the energy load and the maximization of the indoor daylight duration. The method was applied to a dormitory retrofitting. Optimal solutions are the best compromise among antagonistic objectives and would offer guidance to designers in making construction decisions.
Whereas eco-feedback has been widely studied in HCI and environmental psychology, online manual control and automated control have been rarely studied with a focus on their long-term quantitative impact and usability. To address this, an intervention was tested with eighty office workers for twenty-seven weeks. Through the long-term field test, it was found that the addition of online controls in the feedback intervention led to more energy savings than feedback only and worked better for light and phone usage than computer and monitor usage. The addition of automated control led to the greatest savings but was less effective for efficient users than inefficient ones.
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