Variability and associated uncertainty in image analysis for soiling characterization in solar energy systems

The accumulation of soiling on photovoltaic modules and on the mirrors of concentrating solar power systems causes non-negligible energy losses with economic consequences. These challenges can be mitigated, or even prevented, through appropriate actions if the magnitude of soiling is known. Particle counting analysis is a common procedure to characterize soiling, as it can be easily performed on micrographs of glass coupons or solar devices that have been exposed to the environment. Particle counting does not, however, yield invariant results across institutions. The particle size distribution analysis is affected by the operator of the image analysis software and the methodology utilized. The results of a round-robin study are presented in this work to explore and elucidate the uncertainty related to particle counting and its effect on the characterization of the soiling of glass surfaces used in solar energy conversion systems. An international group of soiling experts analysed the same 8 micrographs using the same open-source ImageJ software package. The variation in the particle analyses results were investigated to identify specimen characteristics with the lowest coefficient of variation (CV) and the least uncertainty among the various operators. The mean particle diameter showed the lowest CV among the investigated characteristics, whereas the number of particles exhibited the largest CV. Additional parameters, such as the fractional area coverage by particles and parameters related to the distribution's shape yielded intermediate CV values. These results can provide insights on the magnitude inter-lab variability and uncertainty for optical and microscope-based soiling monitoring and characterization

Soiling in Solar Energy Systems: The Role of the Thresholding Method in Image Analysis

The use of image analysis has often been suggested as a practical way to monitor the soiling accumulated on the surfaces of solar energy conversion devices. Indeed, the deposited soiling particles can be counted and characterized to calculate the area they cover, and this area can be converted into an energy loss. However, several particle counting methodologies exist and can lead to dissimilar results. This work focuses on the role of thresholding, an essential step where particles are distinguished from a background based on the pixel brightness. Sixteen automatic thresholding methods are assessed using 13 200 micrographs of glass coupons soiled at nine locations globally. In low-to-intermediate soiling conditions, the “Triangle” method is found to return the minimum coefficient of variation and a mean deviation closer to zero. On the other hand, methods assuming a bimodal distribution of pixel brightness underestimate the area coverage. In addition, since soiling can be unevenly distributed over a surface, different loss estimations can be returned when the same image analysis process is used on different spots on a sample's surface. For these reasons, image analysis should be repeated at multiple locations on each investigated surface.</p

Soiling in Solar Energy Systems: The Role of the Thresholding Method in Image Analysis

The use of image analysis has often been suggested as a practical way to monitor the soiling accumulated on the surfaces of solar energy conversion devices. Indeed, the deposited soiling particles can be counted and characterized to calculate the area they cover, and this area can be converted into an energy loss. However, several particle counting methodologies exist and can lead to dissimilar results. This work focuses on the role of thresholding, an essential step where particles are distinguished from a background based on the pixel brightness. Sixteen automatic thresholding methods are assessed using 13 200 micrographs of glass coupons soiled at nine locations globally. In low-to-intermediate soiling conditions, the “Triangle” method is found to return the minimum coefficient of variation and a mean deviation closer to zero. On the other hand, methods assuming a bimodal distribution of pixel brightness underestimate the area coverage. In addition, since soiling can be unevenly distributed over a surface, different loss estimations can be returned when the same image analysis process is used on different spots on a sample’s surface. For these reasons, image analysis should be repeated at multiple locations on each investigated surface

DNA Methylation-mediated Down-regulation of DNA Methyltransferase-1 (DNMT1) Is Coincident with, but Not Essential for, Global Hypomethylation in Human Placenta

The genome of extraembryonic tissue, such as the placenta, is hypomethylated relative to that in somatic tissues. However, the origin and role of this hypomethylation remains unclear. The DNA methyltransferases DNMT1, -3A, and -3B are the primary mediators of the establishment and maintenance of DNA methylation in mammals. In this study, we investigated promoter methylation-mediated epigenetic down-regulation of DNMT genes as a potential regulator of global methylation levels in placental tissue. Although DNMT3A and -3B promoters lack methylation in all somatic and extraembryonic tissues tested, we found specific hypermethylation of the maintenance DNA methyltransferase (DNMT1) gene and found hypomethylation of the DNMT3L gene in full term and first trimester placental tissues. Bisulfite DNA sequencing revealed monoallelic methylation of DNMT1, with no evidence of imprinting (parent of origin effect). In vitro reporter experiments confirmed that DNMT1 promoter methylation attenuates transcriptional activity in trophoblast cells. However, global hypomethylation in the absence of DNMT1 down-regulation is apparent in non-primate placentas and in vitro derived human cytotrophoblast stem cells, suggesting that DNMT1 down-regulation is not an absolute requirement for genomic hypomethylation in all instances. These data represent the first demonstration of methylation-mediated regulation of the DNMT1 gene in any system and demonstrate that the unique epigenome of the human placenta includes down-regulation of DNMT1 with concomitant hypomethylation of the DNMT3L gene. This strongly implicates epigenetic regulation of the DNMT gene family in the establishment of the unique epigenetic profile of extraembryonic tissue in humans