Optimize Maintenance With 60Hertz Insights

The purpose of this blog is to exhibit 60Hertz’s groundbreaking research, funded by NOAA’s 2022 SBIR Phase I & II grant. 60Hertz was successfully awarded Small Business Innovation Research funding, also supported by the State of Alaska’s SBIR program to develop our “Clean or Wait” predictive algorithm.

Why is this important? Utility scale solar sites need to be cleaned periodically, especially in the arid West where rainfall does not otherwise clean modules. Yet 60Hertz’s research shows that many asset managers of utility scale or Commercial & Industrial sites do not employ significant analysis on when to clean.

The 60Hertz team successfully developed a powerful algorithm that provides actionable insights as operations directors evaluate this decision to “clean or wait” until precipitation. Thanks to Phase II of the SBIR research, awarded in July of 2023, 60Hertz has further plans to extend the scope beyond this research to other asset classes. The company will commercialize these predictive models.

In this age of data abundance, actionable data from SCADA or Data Acquisition Systems (DAS) layered with other proprietary and publicly available data differentiates a CMMS like 60Hertz’s., Layers of logic create a complex tapestry of information. Now, renewable energy asset owners can take swift action before a costly failure occurs.

 

Project Objectives: Gain a Deeper Understanding of Environmental Conditions That Impact Performance of PV Systems

Weather plays a significant role in solar panel performance and can cause a decrease in efficiency if not managed properly. Renewable energy developers strive to increase generation efficiency by 1-2% across their portfolio. Better maintenance with intelligent foresight is critical to long-term sustainability, operability, and CO2 reduction.

Weather conditions such as dust, snow, hail and wildfire ash can all take their toll on the panels leading to premature degradation. To achieve optimum productivity, companies must ensure regular cleaning and maintenance operations; this often comes with a considerable cost – sometimes upwards of $15,000 – $250,000 per event depending on the size of your generation.

These costs can quickly add up depending on the frequency and mileage of service required, the size of the solar farm and the location. Ignoring data analysis can be costly – like cleaning panels just before the neighboring farmer sprays fertilizers or washing just before precipitation.

Cleaning costs vary depending on design, remoteness and size as well as low maturity levels.

“…The service pricing is defined by companies with poor and low maturity levels. For example [a] site [in remote California] was one of the poorest in terms of being “Solar Panel Cleaning friendly”… this job cost 400% more than a standard carport. When you make a design mistake on a small installation it is a small problem. When you make a design mistake on large installations, then the problem is big. This site had 14,000 solar panels in a very remote location in central California.”

– Carla Dawson, Soliar Technologies CEO.

 

How Is Cleaning Deployment Currently Determined?

  • Human/visual inspection
  • Design cleaning schedule
  • Solar guestimate tools (Excel)
  • Inverter calculates and informs cleaning based on performance
  • Or Asset Managers just don’t clean at all

The last bullet was the most surprising. During our research, it was painfully obvious the industry has an Achilles heel, but market demands are forcing change. Asset owners are realizing their systems are not being optimized, and money is being left on the table.

“The personality of the Director of O&M and his/her problems at a specific time (aka time & circumstances) define the threshold. In general terms, 2% is the minimum value.”
– Carla Dawson, Soilar Technologies CEO

According to the NREL, performance loss due to soiling is estimated to be between 2-25% annually. Making use of reliable and wider-scoped environmental data will minimize or avoid losses and/or critical failures. While the industry chases 1% to 2% gains in efficiencies, there are up to 25% gains at our fingertips.

The NOAA SBIR Phase I program is the first step in achieving these gains. In partnership with Novel Sciences, Sunshare and ScadaSolar, 60Hertz laid the foundation necessary to build a weather-informed maintenance module, which will support operations in a couple of ways.

  • Near-term response to ensure maintenance interventions are timely and optimized
  • Long-term support planning decisions that will optimize design and budget decisions
“If the cost of having this data is less than the money lost due to poor management, then a cleaning algorithm would be successful.”– Carl Dawson Soilar Technologies CEO

“Carla has presented a standard we intend on meeting as we move toward commercialization during 2023”

– Tonya James, COO 60Hertz.

 

NOAA Data

 

Project Findings: Unveiling The Impact Of Environmental Conditions On the “Clean or Wait Decision”

60Hertz’s analysis of the effects of particulate matter on photovoltaic (PV) arrays reveals that extended exposure to soiling caused by adverse weather events such as:

  • Fire – ash
  • Heavy precipitation
  • Atmospheric dust
  • Bird droppings
  • Vehicle or agricultural emissions
  • Volcanic ash
  • Algae or fungi growth
  • Pollen

These weather events pose a serious risk to solar-generated power. Since PV cells require direct sunlight to convert light into energy efficiently, the accumulation of caustic and benign atmospheric particulates can further impede the efficiency of electricity generation from solar energy by blocking sunlight from reaching the panels.

Increased exposure to weather-inflicted soiling accelerates solar equipment degradation. Which significantly impacts reliability and usable asset lifespan, as well as incurs high costs for mobilization of maintenance interventions.

With solar service companies periodically cleaning acres of modules, every speck can have a significant effect on the business’s bottom line. However, making the decision to clean is more complex than you would think. Today, directors make their decision economically, but they are missing data.

Technical Approach

60Hertz utilized a NOAA data set as as an early warning system, to cue on-site validation of the soiling station and any available meteorological (MET) station data to validate if a work order to clean deposited particulate matter is necessary.

This layer strengthens the decisions and moves from reactive maintenance – often weeks delayed, to proactive maintenance – getting ahead of the weather impact if possible.

Through this research, we developed a suite of algorithms converted into modules within our software tools that fuse multiple public and private datasets with features like economics, asset location, weather forecast, etc. to hasten solar service company’s decision times concerning cleaning and/or protecting renewable generation assets.

Our approach also explored relationships (correlative, causal) in the data using Machine Learning, pattern identification and relationship learning algorithms; we also worked with Machine Reasoning visual pattern detection and tracking and then developed models to predict behaviors.

 

Wildfire Ash Scenario

The Marshall Fire in December 2021

To test our hypothesis, 60Hertz teamed up with community solar developer, Sunshare. The experiment evaluated the quantity of ash particulate matter as a result of the Marshall Fire over New Year’s Eve weekend in 2021 near Boulder, Colorado.

Sunshare owns a 5 MW site approximately 50 miles from this generation location. We evaluated if the impact of ash from the fire measurably reduced solar generation during the same time window, independent of cloud-cover or similar generation mitigants.

Behavior Pre-Fire

Data shows the correlation between power output and particulate matter was low; these particles are not present to such an extent that it impacts production levels.

 

Optimize Maintenance With NOAA Data

Behavior During Fire

The Sunshare site generation was reduced by up to 43%, at times,  during this several day window of most intense smoke and therefore ash (particulate matter).

This is consonant with what California’s Independent System Operator observed during the 2020 fires, wherein CAISO lost 30% of solar generation statewide given the high levels of Particulate Matter.  Wherein 114 GW of PV power were anticipated during July of 2020, actual generation fell far short, with the lowest recorded PV generation at less than half of average: 50 GW of solar generation.

NOAA models anticipate that the US will see a 600% increase in fire over coming decades given climate change. As US solar energy production is also expected to accelerate into a greater share of domestic energy production, the algorithms that 60Hertz is developing are increasingly relevant for system operators, project owners, and solar service companies.

Solar service companies should monitor fire impacts on production even miles from an actual fire. While avoiding the impact of ash is impossible, 60Hertz anticipates that timing cleaning with the cessation of smoke, or quantifying the lost production and alerting utility partners, backfilling with BESS generation, or cleaning panels promptly may be actionable recommendations that Operations Directors could consider.

Patent

Thanks to the support of the State of Alaska, 60Hertz worked with Perkins Coie to file a patent on the algorithm and model that we developed during Phase I of the SBIR research.

 

Next Steps: Expand R&D Scope – Informed Predictive Models to Optimize Maintenance Strategies

The 60Hertz team appreciates the value of incorporating NOAA data into our decision support tools. Further work will be conducted to improve existing models used for planning and prototype early warning models for operators to assess the impact and optimize production through data-driven maintenance and operations.

By bringing attention to this problem, 60Hertz has committed to applying for NOAA’s SBIR PHASE II grant program to broaden the scope of this research to explore the impact of environmental and weather conditions beyond panels to inverters, battery container units and the like; all aimed to allow operators to make data-driven decisions that optimize performance.

The 60Hertz team will continue to drive this research to an MVP that supports improved production, reduced maintenance costs, and warranty life for renewable generation companies, ultimately improving resiliency in the grid and the market.

Interested in joining us in this research? Together, we can help build the future of maintenance. Give us a call: (844) 977-4499.

Supported by the National Oceanic and Atmospheric Administration data sets and grant funds from the Small Business Innovation Research program, 60Hertz is delivering groundbreaking research for market innovation in the realm of predictive maintenance based on weather data.

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