Daylighting | EPFL Graph Search

Daylighting is the practice of placing windows, skylights, other openings, and reflective surfaces so that direct or indirect sunlight can provide effective internal lighting. Particular attention is given to daylighting while designing a building when the aim is to maximize visual comfort or to reduce energy use. Energy savings can be achieved from the reduced use of artificial (electric) lighting or from passive solar heating. Artificial lighting energy use can be reduced by simply installing fewer electric lights where daylight is present or by automatically dimming or switching off electric lights in response to the presence of daylight – a process known as daylight harvesting. The amount of daylight received in an internal space can be analyzed by measuring illuminance on a grid or undertaking a daylight factor calculation. Computer programs such as Radiance allow an architect or engineer to quickly calculate benefits of a particular design. The human eye's response to light is

Automated Daylighting Control System based on Sky Luminance Monitoring and Lighting Computing

Yujie Wu

Sufficient daylight exposure contributes to occupants' productivity and health in buildings. However, excessive daylight ingress induces discomfort glare and increases the cooling load in warm seasons. The performance of manual shading systems is limited by usersâ low interaction frequency. Since sky conditions are dynamic, frequent adjustments are necessary, but these are impractical for users to manage. Various shading automation systems have been proposed to better exploit daylight in buildings, the performance of which is limited by a number of factors, including insufficient glare protection, disturbing movement of slats, privacy issues, and commissioning difficulty. In this thesis, an integrated daylighting control system is proposed and demonstrated to regulate daylight in buildings based on real-time lighting computing with the monitored luminance distribution of the sky and landscape, as a decentralized system. First, an embedded photometric device (EPD) was designed and validated for improved accuracy in daylighting simulation compared to standard sky models. The EPD is composed of an imaging system and a microprocessor. After calibration, the spectral response of the imaging system is close to the photopic luminosity function, achieving a 8.9% spectral correction error. The luminance detection range spans 1.2x10^2 ~ 3.78x10^9 cd/m^2, covering extremes of both the shadowing landscape and the sun orb luminance. The EPD monitors the luminance distribution of the sky vault and the ground. Based on the generated luminance map, the EPD is able to perform on-board lighting computing. The performance of work-plane illuminance (WPI) simulation was cross validated with a lux-meter array in a daylighting test module under different sky conditions achieving a mismatch of below 10%. Secondly, since the bidirectional distribution function (BTDF) commonly used in lighting simulation involves bulky data, a compression scheme based on planar wavelet transform was investigated and generic error and the influence on daylighting simulation were also studied at various compression ratios. Results showed that both WPI and daylight glare probability (DGP) are relatively immune to a BTDF compression ratio below 100. Thirdly, an automated Venetian blind was designed which integrates the EPD as both a sensing unit and a controller based on real-time lighting simulation. The EPD determines an optimal shading position according to the simulation results, to offer sufficient WPI, mitigate excessive solar heat gain (SHG), temper discomfort glare, and maximize outwards view. 'In-situ' experiments demonstrated that the automated Venetian blinds were able to regulate WPI efficiently. The expected SHG saving was estimated to reach 47% in warm seasons. It was also demonstrated to mitigate discomfort glare timely, including veil glare from surroundings. A subjective study conducted with 34 subjects showed satisfaction with regulated daylight provision, glare mitigation, and quietness of slat movement. Finally, the EPD was applied to control tint states of a split-pane electrochromic (EC) window to secure occupants' visual satisfaction. Experimental results in a full-scale testbed showed that the WPI was within the confined range with regulated daylighting under clear skies 83% of time and the DGP 95% of the time; under partly cloudy skies, the WPI was within the range 62%~68.2% of the time and for the DGP 85%~94% of the time to achieve visual comfort

EPFL2019

Comparing physical and virtual methods for daylight performance modelling including complex fenestration systems

Anothai Thanachareonkit

Physical or virtual models are commonly employed to visualize the conceptual ideas of architects, lighting designers and daylighting researchers. The models are also used to assess the daylighting performance of their buildings, particularly when Complex Fenestration Systems (CFS) are considered. Recent studies have revealed a general tendency of physical models to over- estimate the performance, usually expressed through work plane illuminance and daylight factor profiles, when compared to that of the real building. These discrepancies can be attributed to several experimental errors. To analyze the main sources of error, a set of comparisons between a real building, a virtual model and a physical model was undertaken. The real building in our case consisted of a full scale test module with a south-facing windows designed for experimentation on daylighting systems. A virtual model was a computed model created in Radiance program while the physical model was a scale model (1:10) of the real case. The fenestration systems considered in this study were a simple window (double glazing) and two CFS (Laser-cut panel and Prismatic film). The physical model was placed in outdoor conditions similar to that of the real building as well as under a scanning sky simulator (for both real sky luminance distribution and CIE standard sky); the virtual model simulations were carried out with the program Radiance using the GenSky function (for CIE standard sky) and the Partial Daylight Factor (PDF) method, the later using the real sky luminance distribution acquired by a digital sky scanner at the same time as the real building's daylight performance was assessed. The daylighting performances of the building, daylight factor (DF) for overcast sky and illuminance ratio (IR) for clear sky, were monitored using illuminance meters: a set of sensors for exterior illuminance and another set of equally spaced 7 sensors placed at 1m intervals starting from the window plane for the interior space were used for that purpose. The interior surface luminance of both real building and physical model was measured using a luminance meter and a High Dynamic Range (HDR) imaging technique (within the Photosphere program). The Radiance program was used to determine the interior surface luminance within the virtual model. The measured performance of the real case, physical models and virtual models were compared, the causes of discrepancies between the real building and models were analyzed. The causes of errors that were evaluated were modeling of building details and dimensions, CFS modeling, mocking-up of the photometric properties (surface reflectance and window transmittance), model location as well as photometer features. To study the impact of these error sources on daylighting performance assessment, virtual models created using the Radiance program were used to achieve a sensitivity analysis of modeling errors. The significant factors were considered, leading to a set of modeling guidelines. The experimental study shows that large discrepancies can occur in daylighting performance figures. For example if glazings are omitted from the model's window, a relative divergence of 25% to 40% can be found at different points in the room, suggesting more light entering than actually measured in the real building. Inaccuracy in window transmittance inaccuracy is a major cause of errors commonly found in daylight modeling. In addition, significant discrepancies can be caused by even slight error in surface reflectance values. Only 10% overestimation of surface reflectance modeling leads up to 80% relative errors in work plane illuminance for a simple window and up to 90% for the assessment of CFS. Continuous sky distribution presented more accurate results than 145 sky sectors simulation, particularly when CFS were evaluated. These discrepancies can be reduced by making an effort to mock up the geometric and photometric features including the daylight simulation of the models carefully. A checklist presented in this thesis can be used as a guideline to help the daylight designers to estimate and avoid errors when assessing daylighting performance.

EPFL2008