Search Results (8)

The Daylight Glare Probability (DGP) includes the luminance of a glare source quadratically, but the solid angle only linearly. While this is in line with formulae of other glare metrics, it must be questioned for small glare sources, if the glare stimulus can no longer be distinguished from larger stimuli causing equal vertical illuminance at the eye, especially in the peripheral visual field. To account for this, the modified version Daylight Glare Metric (DGM) was previously developed. We conducted two studies to evaluate the effect of the modified DGM. First, in a laboratory study under an artificial sky with an LED sun, 35 test subjects evaluated different glare situations. Second, we performed a comprehensive simulation study for an office space, including three locations, three view directions, and 17 window systems (electrochromic glazing, fabric shades). The results from the perception study under the artificial sky provide evidence that the adapted DGM is better suited to predict glare from small, bright sources. The results from the simulation study for a realistic office setting show that, compared to the DGP, the DGM reduces glare ratings for many hours of the year, thus underscoring the practical relevance of improving the DGP formula. Full article

Buildings exchange heat with different environmental elements: the sun, the outside air, the sky, and outside surfaces (including the walls of environmental buildings and the ground). To correctly account for building energy performance, radiative cooling potential, and other technical considerations, it is essential to evaluate sky temperature. It is an important parameter for the weather files used by energy building simulation software for calculating the longwave radiation heat exchange between exterior surfaces and the sky. In the literature, there are several models to estimate sky temperature. However, these models have not been completely satisfactory for the hot and humid climate in which the sky temperature remains overestimated. The purpose of this paper is to provide a comprehensive analysis of the sky temperature measurement conducted, for the first time, in Djibouti, with a pyrgeometer, a tool designed to measure longwave radiation as a component of thermal radiation, and an artificial neural network (ANN) model for improved sky temperature forecasting. A systematic comparison of known correlations for sky temperature estimation under various climatic conditions revealed their limited accuracy in the region, as indicated by low R² values and root mean square errors (RMSEs). To address these limitations, an ANN model was trained, validated, and tested on the collected data to capture complex patterns and relationships in the data. The ANN model demonstrated superior performance over existing empirical correlations, providing more accurate and reliable sky temperature predictions for Djibouti’s hot and humid climate. This study showcases the effectiveness of an integrated approach using pyrgeometer-based sky temperature measurements and advanced machine learning techniques ANNs for sky temperature forecasting in Djibouti to overcome the limitations of existing correlations and improve the accuracy of sky temperature predictions, particularly in hot and humid climates. Full article

Drone-based imaging polarimetry is a valuable new tool for the remote sensing of the polarization characteristics of the Earth’s surface. After briefly reviewing two earlier drone-polarimetric studies, we present here the results of our drone-polarimetric campaigns, in which we measured the reflection–polarization patterns of greenhouses. From the measured patterns of the degree and angle of linear polarization of reflected light, we calculated the measure (plp) of polarized light pollution of glass surfaces. The knowledge of polarized light pollution is important for aquatic insect ecology, since polarotactic aquatic insects are the endangered victims of artificial horizontally polarized light sources. We found that the so-called Palm House of a botanical garden has only a low polarized light pollution, 3.6% ≤ plp ≤ 13.7%, while the greenhouses with tilted roofs are strongly polarized-light-polluting, with 24.8% ≤ plp ≤ 40.4%. Similarly, other tilted-roofed greenhouses contain very high polarized light pollution, plp ≤ 76.7%. Under overcast skies, the polarization patterns and plp values of greenhouses practically only depend on the direction of view relative to the glass surfaces, as the rotationally invariant diffuse cloud light is the only light source. However, under cloudless skies, the polarization patterns of glass surfaces significantly depend on the azimuth direction of view and its angle relative to the solar meridian because, in this case, sunlight is the dominant light source, rather than the sky. In the case of a given direction of view, those glass surfaces are the strongest polarized-light-polluting, from which sunlight and/or skylight is reflected at or near Brewster’s angle in a nearly vertical plane, i.e., with directions of polarization close to horizontal. Therefore, the plp value is usually greatest when the sun shines directly or from behind. The plp value of greenhouses is always the smallest in the green spectral range due to the green plants under the glass. Full article

Walking through street markets is the most popular outdoor activity in Thailand, promoting local economies and tourism. In the year-round hot and humid conditions, living outdoors with long heat exposure throughout the midday can result in heat-related illness. Artificial shade structures and tree shade canopies are typical cooling strategies to protect market sellers and pedestrians from direct sun exposure and improve outdoor human thermal comfort in the street market. This study investigates microclimate conditions and cooling benefits of typical street market shade structures with different settings—three roofing materials, two roof shapes, and surrounding trees with dense and sparse canopies. The dimension of the single artificial shade was 2 m × 2 m with heights varying 2–2.5 m. The vertical air temperature and sky view factor profiles were measured on winter and summer days. The calculated physiological equivalent temperatures (PET) and thermal comfortable hours beneath different shade structures were assessed using RayMan 1.2 software. A cluster of trees with a dense canopy provided more effective cooling (with a satisfied thermal condition of 9 h) than artificial shade structures. Thermal conditions under the galvanized steel roofing and HDPE tarpaulin plastic roofing shades were cooler than those of polycarbonate roofing shade. Meanwhile, the space beneath the sparse tree canopy had the warmest condition. The temperature reductions beneath the artificial shade structure varied throughout the day, with the maximum reduction occurring during midday and the lowest reduction found in the late morning and late afternoon. Our study demonstrates that the tree canopies and artificial shade structures had limited application for providing comfortable conditions throughout midday. To reduce such extreme heat, a combination of shade structures with other cooling techniques is suggested, which should be the focus for further studies. Full article

Daylight is important for the well-being of humans. Therefore, many office buildings use large windows and glass facades to let more daylight into office spaces. However, this increases the chance of glare in office spaces, which results in visual discomfort. Shading systems in buildings can prevent glare but are not effectively adapted to changing sky conditions and sun position, thus losing valuable daylight. Moreover, many shading systems are also aesthetically unappealing. Electrochromic (EC) glass in this regard might be a better alternative, due to its light transmission properties that can be altered when a voltage is applied. EC glass facilitates zoning and also supports control of each zone separately. This allows the right amount of daylight at any time of the day. However, an effective control strategy is still required to efficiently control EC glass. Reinforcement learning (RL) is a promising control strategy that can learn from rewards and penalties and use this feedback to adapt to user inputs. We trained a Deep Q learning (DQN) agent on a set of weather data and visual comfort data, where the agent tries to adapt to the occupant’s feedback while observing the sun position and radiation at given intervals. The trained DQN agent can avoid bright daylight and glare scenarios in 97% of the cases and increases the amount of useful daylight up to 90%, thus significantly reducing the need for artificial lighting. Full article

Ground images with a sky camera have become common to evaluate cloud coverage, aerosols, and energy collection. In parallel, the growth of solar energy has led to an impulse to evaluate and forecast the solar potential in a site before investments, which has increased the importance of solar power measurements. Facing that scenario, this work presents a novel sky camera model that allows to measure the global horizontal irradiance (GHI). Initially, images from a fisheye camera were stored and a pixel-based approach model was created for cloud segmentation. A total of 813 k vectors of features were used as input to the support vector machine for classification (SVC), which yielded a success rate of about 98.6% in accuracy. The Sun’s position was also segmented and an artificial neural network (ANN) regression model for GHI with 17 input features was created based on segmentation of the Sun, clouds, and sky. The training/validation stage of the ANN used 89,964 samples and the test stage reached about 97.4% in Pearson’s correlation. The RMSE was 72.3 W/m² for GHI and the normalized RMSE, nRMSE, revealed 12.9% for GHI. That nRMSE value was comparable to or lower than other studies, despite the high fluctuations in the observed GHI. Full article

Monitoring long-term trends in the evolution of the anthropogenic night sky brightness is a demanding task due to the high dynamic range of the artificial and natural light emissions and the high variability of the atmospheric conditions that determine the amount of light scattered in the direction of the observer. In this paper, we analyze the use of a statistical indicator, the m_FWHM, to assess the night sky brightness changes over periods of time larger than one year. The m_FWHM is formally defined as the average value of the recorded magnitudes contained within the full width at half-maximum region of the histogram peak corresponding to the scattering of artificial light under clear skies in the conditions of a moonless astronomical night (sun below −18°, and moon below −5°). We apply this indicator to the measurements acquired by the 14 SQM detectors of the Galician Night Sky Brightness Monitoring Network during the period 2015–2018. Overall, the available data suggest that the zenithal readings in the Sky Quality Meter (SQM) device-specific photometric band tended to increase during this period of time at an average rate of +0.09 mag_SQM/arcsec² per year. Full article

Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using a Raspberry Pi computer with camera. Reconfigurable for different operational environments, it has been deployed at the National Renewable Energy Laboratory (NREL), Joint Base San Antonio, and two locations in the Canary Islands. The original design used optical flow to extrapolate cloud positions, followed by ray-tracing to predict shadow locations on solar panels. The latter problem is mathematically ill-posed. This paper details an alternative strategy that uses artificial intelligence (AI) to forecast irradiance directly from an extracted subimage surrounding the sun. Several different AI models are compared including Deep Learning and Gradient Boosted Trees. Results and error metrics are presented for a total of 147 days of NREL data collected during the period from October 2015 to May 2016. Full article