From pv magazine 11/2021
The list of damages that severe weather can cause at solar projects is long, and there is still much to learn about the extent of such damage. Hail can shatter glass or send shockwaves through a module, causing cell cracking, losses and degradation. High winds can contort ground-mount installations and trackers in particular, straining and warping mounting systems and hardware. And heavy rainfall, flooding or even consistently high humidity can lead to water ingress and degradation.
Knowing that each weather event presents some level of concern, predicting and preparing for these events has emerged as a lucrative business opportunity of its own, with software and monitoring providers helping solar operators avoid some of these output losses, and generate revenues as a result.
With offices in the French territory of Réunion, Paris and Toulouse, Reuniwatt is a weather forecast service provider, working with a range of solar PV owner-operators around the world. The company offers four main products for solar PV installations: Sky InSight, InstaCast, HourCast and DayCast. They are demonstrating their merit at a project owned by 8minute Solar Energy’s Springbok Solar Cluster.
The Springbok Cluster has a capacity of 443 MW in the Mojave Desert, in Kern County, California. Given its size, passing clouds cover can result in significant generation either ramping up or down. The Springbok Solar Cluster produces on average about 10% of the power needed for the city of Los Angeles, so ensuring maximum production, timely power delivery, minimal curtailment, and advance warnings of potential interruptions is critical.
Through its sensors and digital toolkit, Reuniwatt is providing forecasts of the solar radiation and plant generation for periods ranging from a few minutes in advance, up to several days ahead. The Springbok Solar Cluster utilises single-axis trackers and is paired with a 1.5 MWh lithium-ion battery.
Marion Lafuma, a business development manager with Reuniwatt, provides some insight into how the company’s forecast toolset delivers at the Springbok project. HourCast uses data provided by geostationary satellites to track cloud movements and weather patterns in order to provide intraday forecasts from 10 to 15 minutes, depending on the location and generation of the satellite, up to six hours in advance.
DayCast uses numerical weather prediction models developed by international weather agencies and hybridised with local weather information to improve the forecasts. It also adds additional weight onto the models which perform best on the type of location we’re looking at – there is variance in the performance of each model, dependant on differences in geography and climate. This blend enables weather forecasting anywhere from six hours ahead to up to 10 days.
InstaCast utilizes the Sky InSight weather measurement system. Sky InSight is an infrared all-sky imager giving a temperature reading for a certain area of the sky above the solar PV plant, with the sun being the obvious constant as the hottest point. The camera can then determine any cloud’s height in the sky and its temperature. According to Lafuma, high and cold clouds usually present no issue beyond marginal production drops, whereas low and hot clouds can reduce output more significantly, along with bringing storms with them.
With these offerings, Reuniwatt is able to create a global horizontal irradiance forecast, which gives site irradiance readings down to the square meter, and power production forecasts.
Solar forecasts are critical to the operation of the cluster, allowing it to serve as one of the world’s first fully dispatchable utility-scale solar PV and energy storage projects, its proponents claim. Dispatchable solar power needs to be available at the request of grid operators or the plant owner to match the demands of the market. To meet these requirements, energy storage serves a huge role, providing flexibility to overcome the imbalance between periods of peak solar generation and times of peak demand.
Reuniwatt claims that the high level of forecasting detail allows the operation of the battery to be optimised. It also assists in partially overcoming energy and power issues traditionally linked to solar power variability – such as generation curtailment and frequency variation, while allowing for ramp rate control and energy smoothing.
Another benefit, Lafuma suggests, one he says is often overlooked, is that accurately forecasting battery discharges enables asset managers to prolong battery lifespan, because the number of annual cycles required can be reduced, facilitating the development of more large-scale battery projects.
Predictions of inclement weather with adequate warning for asset operators, also gives those operators ample time to begin their storm mitigation strategies. With time to prepare for a storm along with a prediction of how severe the storm is likely to be, hardware damage and their resulting costs can be reduced. Downtime could also be reduced, as engineering crews wait for replacement parts.
Researchers from Sandia National Laboratories looked into the role for software in mitigating the adverse effects weather can have on PV projects. Their findings were published this year in the journal “Applied Energy,” and importantly, they concluded that the benefits extend beyond damage mitigation as a result of storms.
In the study, Sandia researchers Thushara Gunda and Nicole Jackson combined large sets of real-world solar data and advanced machine learning to study the impacts of severe weather on solar farms. They collected maintenance tickets from more than 800 solar farms in 24 states and used natural-language processing, a type of machine learning, to analyse six years of solar maintenance records for key weather-related words. That data was combined with electricity generation data and weather records from the same facilities to get better insights into what events correlate to production losses.
“One of the main reasons we worked so hard to incorporate the maintenance logs into the analysis, even though we hit a number of blocks along the way, was because, from a qualitative perspective, we work with various industry partners to collect this information,” says Gunda. “And in our conversations with them, we had already started picking up that the way our partners approached storm events differed in the field, depending on what part of the country they were in.”
Gunda said that she and Jackson also looked to identify some of the barriers in the way of meaningful adoption for some of the solar industry’s more cutting-edge technologies. One of the more surprising discoveries that the team made was that snow had the highest impact on energy production. The reason for this, Gunda and Jackson explained, is twofold.
Unlike almost any weather event except flooding, snow sits around long after the storm that dropped it is gone. Every second that the snow covers the PV modules, the production of that asset is significantly reduced. Moreover, the researchers found in conversations with project owner/operators that many operators did not actively remove the snow. Crewed options presented injury hazard risks to workers working in slick conditions, while automated services raised concerns that rocks and other debris might be picked up and damage the hardware.
“The risk that some of these partners have seen in the field, with regards to rocks potentially being kicked up, introduces a bigger risk of the panels potentially being damaged, one that would far outweigh the benefits for them at the time of snow removal,” says Gunda. Leaving snow on top of the panels for a prolonged time, however, doesn’t just pose problems for energy production. Solar systems are designed and constructed to operate under specific load conditions. Adding stagnant weight in the form of snow accumulation, means long-term load on a site not designed to accommodate it.
“The consequence of allowing the snow to remain is that we did see, through the records, a lot of damage to the racking or the framing of the panels from carrying those mechanical loads,” says Jackson. “So you end up with a compounded problem of a loss in generation, and then you’re actually damaging the structure itself.”
The Sandia researchers hope their data will reinforce the idea that site owner/operators should pay more attention to the adverse effects of snow, as the current practice of both action and inaction presenting significant risk is worrisome. They also discovered another interesting occurrence in power generation interruptions when it comes to hurricanes that has had little to do with the physical attributes of the storm. In research, the pair found that some hurricanes contributed to significant production losses even days before they reached the project location.
Jackson and Gunda learned from their partners that, if the county or state issues an evacuation warning for an approaching hurricane, those operators are obligated to shut down crewed sites. With no one available to operate the site, the solar array is forced to shut down entirely until it is safe for workers to return.
One thing the maintenance data couldn’t directly help the researchers glean information from was wildfires. That’s because most references to fire in maintenance logs refer to electrical or operational thermal events rather than wildfires. The researchers did, however, develop a predictive model for the total effect that solar sites in wildfire-adjacent areas might see. For that, they turned to historical wildfire data.
“What we’ve done,” says Jackson, “is we’ve taken PV production data and coupled that with PM data, which is particulate matter, that’s publicly available, along with a couple other weather datasets.”
The researchers knew roughly the date that the fires began and ended, as well as when flames were close enough to affect solar generation via particle buildup in the air and on project hardware. The researchers’ model looks to translate this historical data into predictable metrics, so that owner/operators can account for their project’s distance from a fire, smoke cover, and particulate matter and then calculate an expected amount of lost generation.
The endeavours of the Sandia researchers and the demonstration of the efficacy of detailed forecasting demonstrate how a better understanding of weather impacts, and an ability to prepare for variations and extreme events, can deliver real value to the solar industry. While the weather can’t be changed, it’s best to be prepared for all outcomes.
Author: Tim Sylvia
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