Properties and Performance Indicators of Virtual Natural Lighting Solutions

Several studies have shown that in the built environment, natural light is highly preferred over electrical lighting for its positive effects on user satisfaction, health, and the potential on saving electrical energy. However, natural light is highly variable and limited by time and space. For example, significant fractions of working population in the world do their work during nighttime. Shift workers experience various discomfort issues, and increased long-term risk of some types of cancer due to a lack of synchronisation between the shift work schedule and the worker’s light-dark cycle. Many buildings also have several inside spaces, while admission of natural light into work places is strongly suggested. A possible way to overcome this problem is to develop and apply a Virtual Natural Lighting Solution (VNLS), which is a system that provides virtual natural light, with all of its qualities, which can be integrated inside new and/or existing buildings. One of the first challenges in developing such solutions is modelling their behaviour and predicting their impact on spatial use and performance of buildings. In order to model a VNLS, it is necessary to understand the relevant properties that the solution itself should have, as well as the relevant performance indicators which show how the solution affects performance of buildings where it is applied. For the case of VNLS, the performance indicators of a building will be described in terms of visual comfort, space availability, thermal comfort, and energy consumption. A study is presented, based on literature reviews, in which the properties of currently known artificial windows and skylights are compared to that of real ones. The comparison shows that each existing solutions addresses a subset of all aspects required for a VNLS. The paper concludes by summarising the relevant properties and performance indicators with their expected range of values, which will be the input for developing a computational model of VNLS.