A team of researchers from the Polytechnic University of Madrid (UPM) developed a model to simulate the impact of buildings and objects on direct and diffuse solar irradiance in vehicle-integrated photovoltaics (VIPV).
For their modeling, the scientists used light detection and ranging (LiDAR) equipment, irradiance sensors, and all-sky panoramic imaging.
“The fundamental goal of our research has always been to develop a modeling tool capable of estimating the solar resource on a vehicle's PV surface without relying on any external measuring equipment,” corresponding author, Javier Macias, told pv magazine. “The validation process confirmed that the results provided by the software closely reflect real-world conditions, meaning all necessary inputs for accurate solar resource estimation can indeed be derived from LiDAR data alone, without the need for additional sky imaging or hardware.”
A key aspect of the research involved the use of LiDAR point clouds to generate accurate virtual representations of urban topography. One of the most challenging aspects, according to Macias, was developing algorithms capable of accurately estimating each irradiance component from LiDAR and solar position data.
“The complexity increases when dealing with the reflected irradiance, as it not only depends on the solar angle at any given moment but also on the reflective properties of urban elements,” said Macias. “Although LiDAR data provide highly detailed urban scenes, they do not include the physical properties of objects such as color and material. Finding an algorithm that could estimate the reflected component based only on point clouds and solar data was particularly demanding.”
The experimental setup featured a vehicle parked for a day in winter near the researchers’ laboratory where buildings and trees cause shadows throughout the day.
To model shadows, a shadow factor (SF) was defined to nullify the direct radiation component in case the vehicle is under shadows, according to the team. To model the diffuse component, the visible portion of the isotropic sky is considered expressed through the sky view factor (SVF), and the component is reflected by buildings, according to the researchers, who added that the bright facade view factor (BFVF) is defined to consider the building facades that reflect the direct solar component in a Lambertian manner.
A fisheye camera taking high-quality hemispheric images was placed on the roof of the vehicle, along with a sensor that was developed to measure the irradiance in five directions of the vehicle the bonnet, roof, boot, left door and right door. Measurements were made every minute during the day. A weather station was also installed in the vicinity of the parked vehicle.
Comparisons showed that the shadow effects of buildings could be accurately predicted. “The results show differences of an average of 36W/m2 between measurement and simulation. Furthermore, it is observed that the diffuse component due to reflection on buildings is of the same order as the component due to the sky,” the research group stated.
“Additionally, depending on the position of the vehicle, the effective sky diffuse varies according to the portion of the sky visible, as well as varying levels of irradiance reflected by the buildings depending on the sun's position,” they added.
They also explained that the LiDAR data allows obtaining SVF and BFVF with similar precision to using all-sky images with a relative error of 3% and 4%, respectively.
The research is detailed in the paper “On the validation of a modelling tool for Vehicle Integrated PhotoVoltaics: Reflected irradiance in urban environments,” published in Solar Energy Materials and Solar Cells.
Looking forward, the team wants to test the proposed model in moving vehicles. “We will be collecting irradiance data from a vehicle in motion using our custom-developed sensor mounted on its roof. These real measurements will then be compared with the theoretical predictions generated by the software, allowing us to refine the model for use in moving vehicles and diverse urban environments,” said Macias.
The study was completed at the UPM Solar Energy Institute, where researchers have been developing characterization tools and models that incorporate unique aspects of VIPV such as curvature of vehicle surfaces, dynamic movement, and the influence of urban landscape.
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