Development of a hydrophobic, anti-soiling coating for PV module cover glass

Soiling of photovoltaic modules is a serious problem that significantly reduces power output. The requirements for a hydrophobic anti-soiling coating are discussed and the development of a transparent hydrophobic coating with good durability is described. The performance of the coating has been assessed using optical transmittance, water contact angle and roll-off angle measurements. The durability of the coating is a key issue and the coating has been subjected to laboratory environmental stresses as described in IEC test standards for PV modules. These tests include UV exposure and damp heat exposure up to 1000 hours. Outdoor testing is now underway to confirm these results

The performance and durability of single-layer sol-gel anti-reflection coatings applied to solar module cover glass

A significant source of energy loss in photovoltaic (PV) modules is caused by reflection from the front cover glass surface. Reflection from the cover glass causes a loss of ~4% at the air-glass interface. Only a single air-glass interface can be coated on crystalline silicon solar modules as an ethylene-vinyl acetate (EVA) layer is inserted between the cover glass and the silicon absorber. A single-layer anti-reflection coating (ARC) on the outer surface of the cover glass is effective at reducing reflection losses over the wavelength range of most PV devices. The coating investigated in this work reduces the reflectance loss at the glass surface by 74%. However, the long-term durability of sol-gel coatings has not been established particularly for use in hot and humid climates. In this work, we investigate the damage resistance of a single-layer closed-surface hard coat ARC, deposited using sol-gel methods by applying a variety of accelerated weathering, scratch and abrasion test methods. The reflectance of the sol-gel ARC was measured and then the coating was put through a series of durability and environmental tests. The coating is resistant to damage from heating and can withstand temperatures higher than the phase change temperature of soda-lime glass. Scratch testing demonstrated that the sol-gel AR is relatively hard and difficult to remove from the substrate surface. Pull tests and cross-hatch testing also confirmed the strong adhesion of the coating. Weathering experiments show some degradation in weighted average reflectance, particularly an increase in reflectance of 0.6–0.9% after 1000 h of exposure to damp heat. Testing also showed a vulnerability to exposure to acid. These results indicate that the performance of this type of ARC could deteriorate and possibly delaminate in humid climate conditions The ARC had a low water contact angle, which means the coatings are hydrophilic and, therefore, hygroscopic increasing the risk of water damage over extended periods of time. This work shows that sol-gel anti-reflection coatings are currently unsuitable for use on PV and are unlikely to remain durable across the 25 year industry standard

Advanced Nanostructured Coatings

<p>Advanced Nanostructured Coatings</p

Supplement 1. Code developed to measure riparian buffer width, vegetation height and canopy cover along stream reaches.

<h2>File List</h2><div> <p><b>All files at once:</b> <a href="Code.zip">Code.zip</a></p> <p><a href="funCalcStreamLength.m">funCalcStreamLength.m</a></p> <p><a href="funCalcTransectBufferWidth2.m">funCalcTransectBufferWidth2.m</a></p> <p><a href="funCalculateMEI.m">funCalculateMEI.m</a></p> <p><a href="funCalculateNewXY.m">funCalculateNewXY.m</a></p> <p><a href="funCalculatePointsAlongLine.m">funCalculatePointsAlongLine.m</a></p> <p><a href="funCalculatePointsAlongLine_Reverse.m">funCalculatePointsAlongLine_Reverse.m</a></p> <p><a href="funCalculatepointsAlongLine_Reverse_TransectCenter.m">funCalculatepointsAlongLine_Reverse_TransectCenter.m</a></p> <p><a href="funCalculateRectangleVertices.m">funCalculateRectangleVertices.m</a></p> <p><a href="funFindStreamGrdLidarExtent.m">funFindStreamGrdLidarExtent.m</a></p> <p><a href="funFindStreamVeglidarExtent.m">funFindStreamVeglidarExtent.m</a></p> <p><a href="funPrctile.m">funPrctile.m</a></p> <p><a href="funSampleLidar.m">funSampleLidar.m</a></p> <p><a href="funSampleLidar_forestClass.m">funSampleLidar_forestClass.m</a></p> <p><a href="funSplitStreams.m">funSplitStreams.m</a></p> <p><a href="ProduceFinalTransectData_ForAnalysis.m">ProduceFinalTransectData_ForAnalysis.m</a></p> <p><a href="SampleStreambufferWidth_Mar31_2012_Oct2014_Publish.m">SampleStreambufferWidth_Mar31_2012_Oct2014_Publish.m</a></p> <p><a href="Slidefun.m">Slidefun.m</a></p> </div><h2>Description</h2><div> <p>The ProduceFinalTransectData_ForAnalysis.m and SampleStreambufferWidth_Mar31_2012_Oct2014_Publish.m files are the core code used to process all of the LiDAR data presented in this manuscript. All other code included in this supplement are functions that are called within the two main scripts. Please be sure to save all code files in the same directory. The inputs to both scripts are detailed in the top matter of the scripts.</p> <p>First, run SampleStreambufferWidth_Mar31_2012_Oct2014_Publish.m. The inputs for this script include ground and non-ground lidar point clouds saved in the  "lidarData" directory and a streams data saved in x,y,z format. Please see the code for documentation and examples of all inputs. Other input variables can be defined in the top matter of the code or you may choose to use the default values. All final output will be saved in the "finalResults" folder – included as an empty directory in this supplement. This script will do several things. First it will segment out your stream data into 1,000.01m long reaches. Analyzing smaller segments of stream reduces the file processing sizes and time. Next, the code will use the stream segments to calculate transects within which the lidar data will be analyzed. The final output will be data for each transect that includes its width, and vegetation structure within moving windows as defined in the algorithm. The second script, ProduceFinalTransectData_ForAnalysis.m, takes all of the output from the first script and generate a final matrix that can be used to perform final statistical analysis. This code uses the results in the finalResults folder.</p> </div

Mean differences in meters (Lidar - measured plot average height) for all plots and plots stratified by vegetation type using both percentile and CHM lidar height estimates.

<p>Superscripts (A,B,C) identify post-hoc Tukey test results. Means with the same superscripted letter are not statistically different (P = 0.05).</p

Regression relationships interpolated lidar CHM (CHM_interp) vs. H, non-interpolated lidar CHM (CHMMax) vs. H and h70 vs. H for all plots and for plots stratified by leaf structure type.

<p>RMSE values are standardized relative to the mean for each vegetation type.</p

Regression relationships between measured average canopy height (H) and lidar values using: a) Leaf-off lidar 70^th percentile; b) Leaf-on lidar 70^th percentile; c) Leaf-off lidar IDW Interpolated CHM; d) Leaf-on lidar IDW Interpolated CHM; e) Leaf-off lidar Max Height CHM; f) Leaf-on lidar Max Height CHM.

<p>Regression relationships between measured average canopy height (H) and lidar values using: a) Leaf-off lidar 70^th percentile; b) Leaf-on lidar 70^th percentile; c) Leaf-off lidar IDW Interpolated CHM; d) Leaf-on lidar IDW Interpolated CHM; e) Leaf-off lidar Max Height CHM; f) Leaf-on lidar Max Height CHM.</p

Average coefficient of variation (<i>Cv</i>) values and associated standard deviation of mean <i>Cv</i> for non-ground leaf-off and leaf-on lidar data within all plots and plots stratified by vegetation type.

<p>Superscripts (A,B,C) identify post-hoc Tukey test results. Means with the same superscripted letter are not statistically different (P = 0.05). Within each row, leaf-off Cv values that are starred (**) are statistically different when compared to leaf-on cv values for that row (all plots or vegetation type). Statistical differences are not detected between leaf-on and leaf-off Cv values within conifer plots (p<0.05).</p

Mean differences (<i>D</i>, leaf-on lidar minus leaf-off lidar) between leaf-on and leaf-off lidar percentile height values and associated standard deviation (σ) of mean differences in meters.

<p>ANOVA was not run on 10^th percentile (<i>h₁₀</i>) values due to nonparametric distribution in leaf-off conditions.</p><p>Superscripts (A,B,C) identify post-hoc Tukey test results. Means with the same superscripted letter are not statistically different (P = 0.05). Within each row, values that are starred (**) are statistically different from other values at that percentile within that row.</p

Summary of average plot characteristics within deciduous, conifer and mixed vegetation types.

<p>N = number of plot samples.</p