windows has been shown to improve worker health and productivity [9–11].
To reach their full effectiveness, advanced lighting controls should be incorporated early in the design phase, since they may affect choices such as fixture placement, glazing transparency, or window shading design. Pre-visualizing the realistic behavior of a lighting controller in a particular space in response to daylight and occupancy, as opposed to hypothetical behavior in a generic space, could mitigate complaints of clients whose employees are irritated by the controller behavior or turn off the controller entirely, destroying promised energy savings. Furthermore, with appropriate calibration to real-world physical spaces, a simulation tool could also be used as a benchmarking mechanism for evaluating the performance of lighting control systems in terms of the quality of light generated and energy savings achieved, without the need for replicating the actual physical space hardware. This paper presents a first step in the evaluation of such interactive pre-visualization.
The primary objective of this paper is to evaluate the capability of a combination of offline and online simulation to easily validate and tune the parameters of a candidate lighting control algorithm for a given space. The purpose is to qualitatively evaluate design choices and guide the selection and positioning of sources and sensors. We demonstrate this capability in a series of experiments in a digital simulation of a conference room currently under physical construction, showing how the controller can be easily modified to explore different lighting behaviors and energy use tradeoffs. The result of each experiment is a computer-generated animation of the lighting in a room over time from a single viewpoint, accompanied by estimated measurements of source input, light sensor output, and energy usage.
A secondary objective is to match the simulation as closely as possible to a real physical environment with physical electric light sources and sensors. We demonstrate this calibration in a highly controlled lighting research environment called the Smart Space Testbed, showing how measurements of source and sensor specifications enable the output of the virtual sensors in the simulation to match the outputs of real sensors in the physical room when applying the same control law in both cases. The contributions are aimed at both lighting designers seeking to quantitatively predict real-world controller behavior, and control algorithm researchers seeking to visualize results and explore design tradeoffs in realistic use cases.
Section 2 generally overviews related research on simulation tools for lighting, advanced lighting control algorithms, and the ways in which such algorithms are validated. Section 3 describes the experiments undertaken in this paper and their objectives. Section 4 details the methodology developed to realize the experimental design, including a proposed simulation framework, an advanced lighting control algorithm, and a process for integrating the two. Section 5 reports the results of the experiments and discusses the iterative design process. Section 6 concludes the paper with challenges and directions for future work.