Quantifying PV module microclimates, and translation into accelerated weathering protocols Nancy H. Phillips *a, Kurt P. Scott b

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1 Quantifying PV module microclimates, and translation into accelerated weathering protocols Nancy H. Phillips *a, Kurt P. Scott b a 3M Company, Saint Paul, Minnesota, USA, , b Atlas Materials Testing Technology, Chicago, Illinois, USA ABSTRACT Long term reliability is not well addressed by current standards for PV modules or components, and developing accelerated weathering stress protocols to test the resistance of key components to wear-out is an active area of research. A first step is to understand and quantify the range of actual stresses modules will encounter in the various mounting configurations and in-service environments. In this paper, we use real-world data to benchmark PV module service environments in hot/dry, hot/wet, and temperate environments, with subsequent analysis to translate the microclimate data into a portfolio of practical weathering instrument settings. Keywords: Reliability, stress testing, weathering, photovoltaic, polymer durability, accelerated 1. INTRODUCTION There are many ways to characterize environmental exposures. The authors have been active in international technical standards committees looking at accelerated durability testing of photovoltaic (PV) polymeric materials where the number of opinions on the topic has sometimes seemed even greater than the number of participants. Contributing to this diversity of opinion was the lack of a consensus understanding of real-world module in-service environments. To facilitate the discussion of how best to choose appropriate weathering stress tests, we set out to define a representative range of in-service module environments with characterizations based on real-world data. This is not intended to provide a rigorous quantitative analysis, but rather a process using real-world data and basic weathering science to define and characterize the environmental degradation conditions to which PV polymeric materials are subjected. Reliability of PV module performance is critical for ensuring the financial value of a PV investment. Beyond performance, ensuring electrical safety throughout a module s service life is essential. Recent explosive growth in the industry has led to an enormous cost-down push accompanied by demand for ever more accelerated test methods. In some cases this has been done with an eye toward speed rather than accuracy. For example, one industry standard, the 1000-hour Damp Heat (85 C, 85%RH) exposure has been elevated to longer times or harsher conditions (e.g. the Pressure Cooker test of 121 C, 100%RH) to screen polymeric materials for environmental stability. The stresses introduced in such a test are not remotely relate to real-world conditions and could cause some materials to degrade in a manner which will not occur in field modules. [1] In practice, these extreme heat/moisture test protocols have become a primary tool for screening PV polymeric materials for reliability determination. It is understandable that some false failures of good materials may be a necessary sacrifice for the sake of speed in product development. False positives present a bigger problem if unreliable materials move into the market. A set of reliability tests which relies upon these heat/humidity tests as a proxy for all environmental stresses can be expected to result in some product failures. In particular, long term degradation of polymeric materials by solar radiation, especially solar ultraviolet, is well known, and these stresses are poorly represented in PV standards and qualification protocols.[2] The international standards community is now actively addressing this gap.[3]

2 Both screening and qualification tests require a balanced set of accelerated reliability stress tests in order to achieve truly reliable products at an optimized cost. This will require a rational approach to stress exposures that is correlated with actual field conditions. Within this paper we offer a systematic approach to quantify and bracket the core PV module environmental conditions of solar radiation, temperature, and humidity, and then with the added constraints of practice, utilize those conditions in an accelerated weathering protocol for component PV polymeric materials. Several principles guided this work. To wit: 1) Degradation caused by a stress test should be representative of degradation under real-world conditions. 2) The goal of accelerated stress testing is to receive important performance data in a timely manner. Accurate prediction of a 25-year outdoor service life, for example, is a significant challenge which requires thorough science coupled with appropriate risk management. 3) As a context for qualification tests, methodologies should be materials agnostic and thus applicable for all types of module technologies and component materials. The levels and combinations of stresses should impact materials non-selectively, as nature itself does. 4) The bulk of solar radiation driven material degradation is believed to occur during the period a few hours before and after solar noon. Defining a steady state environment representative of this time period is a useful way to compare the stress driven by solar radiation at different locations. 2. BENCHMARKING PV MICROCLIMATES The term microclimate as used in this paper describes the in-service environment of polymeric materials contained within a PV module. This local environment arises from a combination of climate conditions and factors specific to the application, as will be described below. The effort described in this paper focused on defining a generic steady state condition representative of the solar degradation conditions at particular location/application combinations. Real-world data for targeted sites are presented and analyzed in separate sections below, focused on solar irradiance, temperature, and humidity. 2.1 Site designations. Geographical locations were selected to bracket the range of environmental stressors of heat, humidity and irradiance. Hot/dry and hot/wet sites were targeted as well as a temperate location to provide a baseline. Consideration of other relevant environmental stresses, for example, the mechanical stresses that come with thermal or freeze/thaw cycles, sandstorms, etc., were intentionally left for a future effort. Within the broad array of possible locations, the following were selected based on the availability of climate data: Phoenix (hot/dry), Miami (hot/wet), and Sanary, France (temperate). Application specifics work in concert with the climate to define the in-service stresses. Two primary distinctions come from the module s angle of exposure and the structure to which the module is attached, e.g., a roof, fixed rack, or solar tracker. The angle at which a module faces the sun will affect the irradiance level and temperature; the module construction and mounting conditions define the thermal insulation properties, and thus the module temperature. This analysis utilized a glass/backsheet module construction, and considered two mounting types: rack (south facing, latitude tilt, open back) and flat roof (south facing, 5 degree tilt, insulated). For the purposes of this paper, a site will refer a specific combination of geographical location and mounting type. The six target sites are shown in Table 1. In the sections below, descriptive climate data for each of the locations is reviewed and paired with the in-service parameters to provide a set of characterizations for each of these sites. It is an emphasis of this work that real-world data be used to provide a frame of reference. Climate data came from Atlas.[4] Where used, other real-world sources are listed with the data.

3 Table 1. Benchmark sites Climate Zone Location Mounting Type Hot/dry Phoenix, Arizona, USA Latitude Rack (34 ) Hot/dry Phoenix, Arizona, USA Flat Roof (5 ) Hot/wet Miami, Florida, USA Latitude Rack (26 ) Hot/wet Miami, Florida, USA Flat Roof (5 ) Temperate Sanary, France Latitude Rack (45 ) Temperate Sanary, France Flat Roof (5 ) 2.2 Solar Irradiance Solar irradiance levels in the real world are impacted by a variety of factors, including time of day, latitude, elevation, cloud cover, humidity, time of year, etc. Two parameters are important with regard to solar-related materials stress at a specific location. The maximum solar irradiance is typically observed at solar noon around the summer. The second is the amount of accumulated irradiance or radiant dosage over a year. Solar dosages in this paper are reported for two wavelength ranges: Total Solar refers to the total integrated value measured over the range 300 nm 3000 nm, and TUV data refers to a range of 295nm nm. The irradiance data for the target locations is displayed in Table 2, with the several solar noon values on different dates included to show the seasonal variance. Annual values for latitude and 5 degree exposures are included to characterize the Roof and Rack exposures. Location Appl. Type Exposure Angle Table 2. Solar data Typical Maximum Irradiance Total Solar at Noon (W/m2) 3/21/2001 6/21/ /21/2001 Annual Total Solar (MJ/m2) Annual TUV (MJ/m2) Desert (Phoenix) Rack Latitude: Desert (Phoenix) Roof Hot/Wet (Miami) Rack Latitude: Hot/Wet (Miami) Roof Temperate (Sanary, FR) Rack Latitude: Temperate (Sanary, FR) Roof Note: These are irradiance values are meant to be used as a rough comparison of solar insolation at each location. They were measured on specific dates in a particular year and represent only a snapshot of the of solar irradiance values in each location. With annual climate variation and measurement instrument uncertainty, other measurements taken under similar circumstances could vary significantly.

4 Total UV ( ) Irradiance (W/m 2 ) This data was used without further interpretation for the front side module irradiance values at each site. Defining a benchmark characterization metric for backside solar exposure is more complicated. Local site details, for example, ground cover and degree of shadowing, will impact the amount of diffuse and reflected light. Different positions in an array field (edge, center) will have different exposure levels. In order to have a real-world reference on this question, front-side and back-side irradiance data were measured over one day on an unshadowed rack- mounted module positioned over gravel. Figure 1 shows the front side and backside values and their ratio during the course of the day. At solar noon, the back side irradiance was only 7% of the front side value. Much higher percentages are observed at dawn and dusk, but at less relevant low irradiance levels. The accumulated value over the day was 10%. As a gross approximation, the typical maximum value for backside irradiance typical max and dosage levels for each of the locations was estimated by taking 10% of the direct solar data for each of the sites. Gathering data to explore the range of possibilities is left for future work Solar Irradiance for Sun facing versus Ground facing side (AZ fixed 34 degrees, ) TUV - Sun facing TUV - Ground facing TUV ratio: Ground Facing/Sun facing 30% 25% 20% 15% 10% 5% 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 Time-of-Day 0% Figure 1. Front side and backside irradiance levels (3M data[5]) 2.3 Temperature Each of the targeted locations has its own daily and seasonal temperature variations, shown for Miami as a plot of daytime hourly temperatures over one year in Figure 2A. Average and annual high temperatures are common characterization metrics, but neither is appropriate to use as a typical maximum value. To translate each location s temperature variance into a composite typical maximum temperature, the hourly temperature data from one year was analyzed as shown in Figure 4B. The cumulative hours at each temperature is plotted as a function of temperature, so that the 50 th and 100 th percentile values represent the average and maximum temperatures, respectively. The 85 th percentile value was designated as a reasonable approximation for the typical maximum temperature for each location. By this analysis, typical maximum temperatures for Phoenix, Miami, and Sanary were established as 42 C, 33 C, and 27 C, respectively.

5 Figure 2. Miami daytime hourly temperatures over one year. A) plotted versus time, B) cumulative plot Module temperatures at each location are strongly impacted by the module IR absorption and the level of thermal insulation afforded by the module and mounting structure, additive to the air temperature. This analysis is based on a typical c-si module with glass/backsheet construction. Both roof and rack mounts are considered. Figure 3 demonstrates the contributions of air temperature and irradiance on module temperature. Note that the peak module temperature occurs closer to solar noon than to the daily temperature maximum. Also shown is the Black Panel Temperature (BPT), a common weathering facility measurement, which correlates closely to the module temperature. Figure 3. Comparison of air, module, and Black Panel Temperature (3M data) A typical maximum temperature for the rack-mount sites was defined by analyzing the annual BPT data for each of the sites in the same manner as the air temperatures. By this analysis, typical maximum temperatures for the Phoenix, Miami, and Sanary sites were established as 55 C, 49 C, and 44 C, respectively. For the roof sites, a parametric model developed by Tamizhmani for building-applied PV was used.[5] This model uses irradiance, ambient temperature, and wind speed as input parameters (Eq. 1).

6 Ambient T % Relative Humidity Tm= W 1 (Irrad) + W 2 *Tamb + W 3* WindSpeed + C (Eq. 1) The typical max air temperatures were used as the temperature inputs for each site, along with the solar noon irradiance. Wind speed was set to 0. The inputs and calculated values are shown in Table 3. Note the large differences between the roof and rack temperatures for each location; they offer very different design targets for PV polymeric components. Table 3. Modeling parameters and site characterization temperatures Irr (W/m2) Typical maximum Tamb ( C) C Typical Maximum Tmodule ( C) model W coefficients 1 = W 2 = Phoenix Miami Sanary roof rack 2.4. Humidity RH varies throughout the day, as shown for a typical day in Florida in Figure 4. The important metric for this analysis is the Absolute Humidity (AH), i.e., the moisture content in the air, needed to calculate the RH at the module. Whereas RH changes significantly throughout the day, AH is more constant. For the purposes of this study, the average of the two AH values shown in each figure was taken as representative for AZ and Fl, respectively, without further review of climate data. A value for Sanary was taken from the Atlas data for midsummer. These values ranged from 9 g/m3 to 17 g/m3. For comparison, the AH of Damp Heat (85 C/85 %RH) is 300g/M3. The typical maximum RH values at the module were obtained for each site by converting the moisture content into an RH for each typical maximum temperature (Table 4) Florida, August 12, 2013 Ambient Temperature RH(%) AH (g/m 3 ) Tmax Tmin Relative Humidity Arizona, July 2013 C Ambient %RH 45 Blk Pnl C 10 RH(%) AH (g/m 3 ) Tmax Tmin :00 4:48 9:36 14:24 19:12 0:00 4:48 Figure 4. Temperature and Relative Humidity for Florida and Arizona. Data from Dhere [7] and 3M [5]

7 Table 4. Site Humidities. site Typical Max T (amb)( C) %RH (Typ Max T) AH (g/m 3 ) Mounting Type Typical Max T (module)( C) T module AZ Rack Roof FL Rack Sanary Roof 69 8 Rack Roof Summary of PV Module In-Service Module Environment Characterizations. All of the characterization metrics developed for each site are summarized in Table 5. Comparing the data between the sites, it is interesting to note which parameters vary, and which do not. The typical maximum irradiance levels are comparable for all three sites, and the annual solar dose are similar for Phoenix and Miami. At the elevated temperatures of the modules, the RH values range from low to extremely low, all well outside the range of the Damp Heat test. The temperature differences are the most striking, and a reminder that the amount of solar induced degradation is a combination of stressors. An adequate temperature factor must be included with the irradiance level to recreate the typical maximum stress environment. In a broad sense, there are some surprising implications in this data. The previous section dealt with the learnings regarding RH at the module which shows how much the damp heat test deviates from real-world conditions. Secondly, the Arizona roof module temperature is generally higher than that in most testing protocols. The contrast between the rack and roof applications is stark, particularly from the backside perspective. For the backside, the environmental stress on a roof mount includes high heat and no light, whereas on a rack mount, the heat is lower and the light is significant. Table 5. Summary of PV Module In-Service Module Environment Characterizations. Location Appl. Type Typical Max T Max Irr TUV ( C) RH (W/m2) (annual) (module) MJ/m2 amb module front back front back Desert (Phoenix) Rack Desert (Phoenix) Roof Hot/Wet (Miami) Rack Hot/Wet (Miami) Roof Temperate (Sanary, FR) Rack Temperate (Sanary, FR) Rack

8 3. TRANSLATION INTO AN ARTIFICIAL WEATHERING PROTOCOL One approach to developing a weathering stress exposure could be to incorporate the combined worst case conditions into a single exposure under the assumption that modules are not differentiated today and should be qualified thereby to work in all anticipated conditions. The analysis presented here challenges this approach, and suggests that multiple weathering protocols may be appropriate to reflect the differences in climate and mounting environments. Artificial exposures for roof and rack mounts will be considered separately. Two sets of typical maximum weathering instrument set points are described which match the worst case scenarios for roof and rack, respectively, with an additional exposure added to match the rack sites to represent back-side exposure.(table 6, Exposures 1-3). These are described below, with several modifications based on practical limitations. Temperature is set at the Arizona roof (95 C) and rack (65 C) typical maximum module temperatures. The site humidity levels challenge the lower level limit of conventional weathering instruments and thus RH is not specified or controlled. Defining an irradiance set-point first requires the specification of a light source, and then conversion of the typical max solar irradiance to a light source based value. A filtered xenon (Xe) arc light source is used here as most representative of the solar spectrum. Conversions to other light sources are more complicated because of the spectral mismatch. The typical front-side maximum irradiance levels for each site are very similar, and translate to a Xe (340 nm) set point of 0.7 W/m2/nm for the front side. For the back side, the solar noon irradiance level (0.07 W/m2/nm) is below the minimum level attainable in typical weathering instruments, and so a minimum value 0.35 W/m2/nm was used. An alternative approach is to use the same irradiance set-point as for the front side so that the same weathering instrument can be used for all materials under test. (Exposure #4). Duration of test exposure is a difficult to establish. The hours to get to a service life dosage are easy to calculate, but in practice, there is no fixed conversion factor. They do serve as a reference point. The hours to get to the front side 25 year service life dosage add up to years of artificial exposure. A correlation to years in the field can only by determined by comparison to field exposed samples. Table 6. Weathering exposure settings corresponding to typical maximum in-service characterization environments Application ChT( C) Ch RH Xe (340) (W/m2/nm) Exposure #1 Roof - front 95 nc.7 Exposure #2 Rack - front 55 nc.7 Exposure #3 Rack - back 55 nc 0.35 Exposure #4 Rack -back (alt) 55 nc.7

9 4. CONCLUSIONS We have presented here both a method to characterize the microclimate stress of the in-service PV environment using real-world data, and a representative set of data for a range of location and mounting combinations. The purpose is to create a context to allow a rational and balanced approach to accelerated stress testing of PV polymeric materials. This effort only considered a qualitative steady state stress model, and is intentionally material agnostic. Our intention is that this be a tool used in the creation of a rational set of accelerated environmental qualification testing that will balance the needs for speed in product iterations with good risk management in the development of reliable products. The fundamental tenet of this paper is that conditions used for accelerated environmental stress testing should have some established relationship with the real world. The typical maximum conditions described here aim to provide results that will likely correlate to field conditions, and are offered as a lower risk approach to testing. We are not adverse to higher exposure levels that can screen materials more quickly. It must be recognized that with increased speed comes decreased accuracy that must be managed carefully. A fast test that misses key stressors may result in field failures, and fast tests that accelerate all stressors may result in over-engineered products at higher costs. Different approaches may well be taken for screening and qualification testing. A balanced approach is recommended. We stop short of recommending a specific exposure setting for the industry to use for qualification testing. To suggest an aggressive test which might exclude current products without some data is the not the tone of this paper. Given the extended outdoor service life requirement, the industry must move to understand the limits of acceleration that provide good results. This should happen in steps, and those are beginning to occur. A final step in the analysis is to reference a weathering exposure for PV component material discussed with this analysis as background data. Qualification Plus[7] contains a set of tests including weathering tests designed to fill gaps in module and component reliability testing. The authors were active participants in the discussions leading to the recommendation for a back sheet weathering test, for which the analysis here provided a basis. We will not attempt to capture all of the discussions, but offer it as the product of a discussion informed by this analysis. Table 7. Qualification Plus back sheet weathering exposure settings Material Backsheets - front side Backsheets - back side DF (W/m2/nm) ChT RH BPT hours C 50% 70C 4000 ACKNOWLEDGEMENTS While the authors gathered and packaged the data, we want to acknowledge the oversight and contributions of members of the numerous others in the community, in particular the members of the IEC TC 82 Weathering /Backsheet group. We particular appreciate many hours of discussion with David Burns, 3M, and for his technical support in reviewing this document.

10 REFERENCES [1] J. Jones, M.J. Shiao, PV Module Reliability Scorecard GTM Research Publication, July 2014 [2] IEC Standards Photovoltaic (PV) module safety qualification -- Part 1: Requirements for Construction, 2004; PHOTOVOLTAIC (PV) MODULE SAFETY QUALIFICATION -- PART 2: REQUIREMENTS FOR TESTING (2004) [3] Ongoing work of The International PV Quality Assurance Task Force, [4] Atlas Materials Testing [5] Personal communication from David Burns, 3M [6] Oh, J, TamizhMani, G., Palomino, E., Temperature of Building Applied Photovoltaic BAPV: Air Gap Effects Proc. SPIE 7773 (2010). proceedings.spiedigitallibrary.org/proceeding.aspx?articleid= [7] Personal communication from Neelkanth Dhere, Florida Solar Energy Center, University of Central Florida [8] Kurtz, S., Wohlgemuth, J., Kempe, M. Bosco, N., Hacke, P., Jordan, D., Miller, D., Silverman, T., Phillips, N., Earnest, T., Romero, R., Photovoltaic Module Qualification Plus Testing, NREL Technical Report, December 2013www.nrel.gov/docs/fy14osti/60950.pdf