To address these limitations, future studies should incorporate validated, evidence-based instruments to measure suicide risk, such as the Suicide Probability Scale or the Suicide Inventory Questionnaire , which have been cross-culturally validated for use in Native American contexts . Validated, evidence-based instruments to measure the selected predictors should also be incorporated. Another limitation of this study is the need for further expansion and validation work to optimize its accuracy before deploying it in a clinical setting to improve clinical decisions. For example, the model’s transportability to Native American youth in different settings outside of California should be evaluated via external validation. The model’s development sample comprised participants from a non-randomized study, which may not be generalizable to Native American young people not in a public high school setting. Future studies may also benefit from incorporating a longitudinal design of the data to substantiate temporal precedence beyond the single academic year evaluated in this study. Furthermore, a limitation of the study is that it relied on existing data from a survey whose questions may not fully capture the relevant factors. Further research should investigate whether the model’s predictive value could be improved by adding other factors such as predictors in the spiritual-historical domain, which is absent from CHKS. One example includes the Historical Loss Scale , which is a validated instrument designed to measure historical trauma. Before using the risk scores in practice, the clinical utility of the model and its feasibility and acceptability need to be measured. Although a factor may be statistically significantly associated with suicidal ideation, as seen in previous research, grow trays it may not necessarily have predictive power and not contribute to predicting suicidal ideation in new cases as indicated by the subset of predictors excluded after lasso regression.
As such, even though foster care placement was not retained as a predictor in the final model, future studies should still consider this risk factor in conceptualizing suicide-related behavior. Despite these limitations, the study’s main analyses comprised 438 participants with the outcome and 10 potential predictors, which conforms to the minimum of 10 events per predictor variable required for reliable prediction modeling . Moreover, a robust 10-fold cross-validation was utilized for internal validation, which produces less biased estimates than split-sample validation, resulting in more confident predictions . Efforts to improve the reliability of solar photovoltaic systems have, to date, largely focused on the core components of modules and inverters. With weather-related damage becoming a prominent industry issue, the importance of failures with other array components such as racking, fasteners, and wiring systems now deserves industry attention. The entirety of the solar PV system must be examined for reliability. Statistically significant datasets of storm-caused failures validate and inform our understanding of weather effects and clarify conclusions and corrective actions. Emerging patterns of field failures as reported by stakeholder groups are beginning to provide evidence of current inadequacies in design, construction, and operations. These patterns of failures also are revealing ways to improve performance and durability related to severe weather events, which would help ensure that solar PV systems can be used as a resilient power source in diverse climates. The ability of the solar industry to incorporate lessons learned in a timely manner is essential for continued technological and financial advancement. Many industry stakeholders now have direct experience with weather impacts and have gained valuable insights into root failure modes, cost impacts, and performance and availability reductions.
These insights comprise critical lessons learned that should be widely shared, yet many firms keep this information private. Lack of dissemination of storm-damage data are a central barrier to widespread resolution of these issues. Current industry practice reflects a wide variety and immaturity of codes, standards, and design principles that result in unpredictable long-term operational outcomes. Intense price pressures, along with many new industry entrants and exits, may provide some explanation. There is a wide variation in the understanding and application of codes and standards, design practices, construction methods, and operations. Most important, many engineers lack awareness of where serious code gaps exist and how to compensate for them. Similarly, buyers of manufactured racking systems are unaware of the design flaws inherent in the products they are procuring for a project. There are many examples of code-compliant arrays that did not withstand forces of even routine weather events such as summer thunderstorms. The goal of this report is to provide an operations-focused synopsis of how solar PV systems are affected by both severe and regular weather events. The findings are drawn from an existing body of small research efforts and field observations that have implications for the design, construction, and operations life-cycle phases of a solar array. Nearly every location in North America experiences at least one form of severe weather . During the 30-year operating period of a solar PV system, it is statistically likely that a significant weather event will strike. Impacts stemming from severe weather events appear to present a serious hindrance to the continued advancement of solar PV as a resilient, cost competitive, and dispatchable energy source. Insurance data supports the assertion that weather-related impacts should be a serious industry concern.
Insurance data are tied closely to weather events, but an examination of insurance claim data is often very sensitive to the time period selected. Years may go by with no problems, but a severe weather event like a hurricane or hailstorm will affect a large number of systems all at one time. A research report by GCube, a leading insurance underwriter in renewable energy, highlights that weather-related losses are a leading cause of solar PV claims worldwide. Events such as tornadoes, floods, windstorms, and hail damage have all contributed to damages. From 2011 to 2015, weather-related events accounted for 49.8 percent of all insurance claims . There are regional differences in these claims; within North America, approximately half of all solar PV claims are attributed to weather impacts, while the global percentage is approximately 25 percentage . Generally speaking, there has been a significant increase in weather-driven PV claims in the last five years . The report also identified key factors that influence the financial impact, as well as recommendations for preventing failures in the future. Another analysis of insurance claims indicated losses to solar equipment using claim information from Verisk, a leading compiler of property-casualty loss data. It showed that 95 percent of the 15,128 claims over the period of 2014 to 2019 had weather-related causes. Figure 1. Of those weather-related causes, the most frequent cause of loss was from hail , the second most frequent cause was wind , and the third most frequent cause was fire . The largest average claim size for losses including solar equipment was from fire , followed by lightning . The fire claims in this collection of data concentrated around the dates of three large California wildfire events — indicating the significance of losses from these events.Peer-reviewed literature encompasses both experimental and field-related analysis regarding different influences of weather on PV systems. For example, Santhakumari and Sagar provided a comprehensive review of the impact of different environmental conditions on PV module performance. With regard to extreme weather events of snowfall and ice buildup, the authors noted that orientation and tilt angle of the modules can greatly influence the amount of production loss . Hail damage can also lead to power loss; up to 30 percent, due to impact cracks affecting electrical performance . A number of snow events were also documented in the Northeastern United States, leading to significant under performance in the region in 2011 . Andrews et al. monitored the PV system for two winters in Canada and determined that the losses due to snowfall were dependent on the angle and technology being considered. Over the two years studied , pruning cannabis the losses ranged from -3.5 to +1 percent of expected yearly yield for sites in southeastern Ontario. The increase in expected energy was attributed to increased albedo for modules with higher inclinations . Heidari et al. quantified energy losses of PV systems with different architectures, and tilt angles were quantified for a test site located in Calumet, Michigan. Based on their study, the authors found that snow-related energy losses ranged from 5 to 12 percent for three unobstructed, elevated modules, and from 29 to 34 percent for comparably tilted modules mounted next to the ground .
Although many of the researchers documented the influence of specific ambient conditions on PV systems , the primary discussions for extreme conditions are generally limited to a survey of damages observed for a general event. For example, Ghazi and IP noted that precipitation higher than 12 millimeters and wind speed lower than 30 kilometers per hour led to poor efficiency of PV panels in the southeast United Kingdom. However, this level of specificity is generally lacking in evaluation of extreme weather events, with limited information presented regarding the quantity, timing, or dimensions of the extreme weather events that led to specific PV system impacts and damages.The field observations reported here were documented by both U.S. Department of Energy laboratories and industry. The field-observed failures and a summary of the root cause failures is provided. The full list of field failures observed and discussed in this report is limited to examples that are considered by the authors to be the most common and serious, therefore, this is not a comprehensive list of field-observed failures. While this chapter presents an introductory overview, failures and losses from specific weather events are discussed in greater detail in subsequent chapters, and more suggestions for improvements are offered. Various aspects of PV projects can contribute to their failure, ranging from materials and people to codes/standards and business models. In a 2018 study, the Rocky Mountain Institute conducted field visits to investigate the root causes of PV system failures and survivals within the same region. They documented a number of recommendations to improve the resilience of PV systems during hurricanes . Failures during hurricanes were attributed to orientation issues, training, and module mounting hardware. For example, the report notes that systems that survived had bolted modules and lateral racking supports . The authors noted that in addition to specifying the different hardware used, collaboration is also needed to ensure that module, racking, and equipment suppliers are implementing representative load tests and are documenting associated assumptions . Specifications and construction guidance recommendations have also been made for rooftop systems, including the use of mechanically anchored PV rails and use of rated locking panel clamp bolts .Wind is the most common damaging element stemming from nearly every significant weather event. Design engineers use simple wind speed values plugged into software tools or hand calculations that are done to meet required codes. These simple wind speed values do not capture the unique wind dynamics that stem from different weather events, and thus the design of solar PV structures lack consideration of the highly dynamic forces that result from different storm types. Comparing, for example the wind speeds and resulting damage between hurricanes, tornadoes, and derecho events illustrates the need for engineers to adapt updated design practices. Even an F-0 rated tornado on the Fujita scale of less than 73 mph can easily destroy a solar array, while the same wind speeds from a hurricane or routine thunderstorm would do little damage. This is due to the high-pressure differentials generated by a tornado over a short distance with strong updrafts inside rotating winds. Similarly, there appear to be unique and dynamic forces stemming from the powerful down burst clusters generated with derecho thunderstorm events. More investigation is needed to fully characterize wind forces from different storm events, and these insights must be used to inform and update design practices.System owners and operators may be working under the false assumption that the bolted joints, fasteners, and racking systems can withstand the design wind speeds used to meet ASCE-7 code. Field evaluations of damaged arrays indicate failures are occurring at well below design wind speeds. Currently there appears to be poor correlation between design wind speed and actual wind speeds in terms of the survivability of solar structures. Some engineers have recommended the use of stamped structural drawing sets as a solution; however, there are concerns that the engineering process itself and underlying supporting calculations and software modeling tools need to be updated.