Protect solar energy assets from the weather

According to the US Energy Information Administration, between 2020 and 2035, solar energy is expected to grow from 3% to 14% of total energy production in the United States. By 2050, this particular renewable energy source could account for 20%.

Along with this optimistic outlook for clean energy, rainfall events are likely to become more extreme, based on the Intergovernmental Panel on Climate Change (IPCC) Assessment Report 6 (AR6). ), extensively peer-reviewed.

Protecting photovoltaic panels against hazardous weather conditions such as extreme winds and hail events will be important for the availability and reliability of solar energy.

Limited period of occurrence, Significant costs

Particularly large hailstones can damage solar panels, both exterior and interior (micro cracks), resulting in sub-optimal performance of output power efficiency. Over the long term, the functionality of the panel may deteriorate further as dust or water enters these cracks.

In the northern hemisphere, the period of occurrence is mainly limited to April to September. Some areas are more prone to hailstorms than others. However, many areas of the United States with the greatest potential for solar power generation are the same areas most prone to hailstorms.

Figure 1. The US NWS Storm Prediction Center map shows that Texas, Oklahoma, Kansas and Nebraska are most at risk, with some parts experiencing hailstorms with hailstones >2 inches with a frequency of more than one day per year. Image reproduced with the kind permission of NOAA.

As large hail events remain rare, the damage they cause can be very significant for solar power assets. Due to a combination of a historic correction and recent cases in Texas, solar insurance prices are skyrocketing – increasing as much as 400% in recent years – to a $1 million deductible and a physical damage limit of 15%.

Previously, insurance policies with a minimum deductible of $100,000 or 5% of the physical damage limit were common. Today, a deductible of $250,000 and a limit of 5% are not uncommon.

Maximum physical damage limits are increasingly being defined in policies instead of full physical damage coverage.

Seeking cost control, utilities are turning to weather data to protect their assets. Providing actionable information increases awareness of potential hail damage and preparation times.

What would you do with up to 3 days notice?

With a forecast time of up to 3 days, operators and field crews can monitor and prepare assets for risk.

The use of Numerical Weather Prediction (NWP) models in addition to several model parameters, instability indices and simulated radar reflectivity can provide indirect indications of hail occurrence. Several good models are available in the public and commercial domain.

freely available statistical models that help to determine the occurrence of hail, source Johan Jacques, KISTERS AG

Table 1. Freely available statistical models that help to determine the occurrence of hail, (Freely available statistical models that help to determine the occurrence of hail, source Johan Jacques, KISTERS AG).

Besides the classic model parameters, the HRRR (High Resolution Rapid Refresh) model also produces an interesting parameter called GRMAX01, which provides one-hour predictions of the last hour maximum hail/graupel diameter at the surface.

The NAM and HRRR models proposed above are deterministic, while SREF provides ensemble data that can be used to derive the probability of severe weather events. Note: Settings such as jitter/hail (especially for HRRR outputs) are considered experimental.

What would you do with up to 2 hours notice?

With 0 to 2 hours in advance, protective measures can move the solar panels to a safe position, reducing damage from large hailstones. In addition to the aforementioned NWPs, nowcasts—short-term forecasts using observed radars and advanced extrapolation algorithms—based on X-band type polarimetric radar installations can support decisions.

X-band radars typically have a usable radius of 30 to 60 km (19 to 37 mi). Besides the classic parameters such as reflectivity and precipitation intensity, radars provide reliable information on the type of precipitation reaching the surface, including summer hail.

X-band radars also have the advantage of high resolution and high update rate.

By combining precipitation type with nowcasting techniques and applying warning thresholds to this data, a hail early warning system can be established to mitigate damage and increase system resilience.

Figure 2. Example of X-band radar precipitation pattern, set to 125 m resolution. Red pixels indicate areas with large occurrences of hail. (Screenshot of precipitation radar data from X-band radar, set to 125 meter resolution. Red pixels reveal areas with large hail occurrences. | Image source Johan Jacques, KISTERS AG.)

Lessons to be learned from each event

After a storm has occurred, the ability to prove that large hail has fallen on the utility site becomes crucial. Some parametric insurance based on agreed thresholds is emerging. For example, a policyholder may need to document the presence of hailstones larger than 2″ in diameter.

In addition to the evidence provided by X-band radars, on-site hail sensors are essential. At a minimum, they should provide good statistics on the distribution of hailstone size over time and the number of impacts per hail size class per event.

Figure 3. Distribution of hail diameter over time during a hail event.

Although hail events remain rare, the exponential growth of data from a utility’s weather sensor network, forecast centers and X-band radar providers establishes the need for a reliable platform to display this information, set alarms on conditions and store for event-driven post-analysis.

The KISTERS Data Sphere not only integrates data from an organization’s monitoring network with forecasts and nowcasts from external sources, but Hyquest Solutions America, a KISTERS Group company, also provides end-to-end hail sensors. tip and nowcasting technology.

As a career meteorologist, Johan Jacques leads the conceptual development of the HydroMaster high-resolution precipitation information service. Working closely with water companies, energy utilities and network operators allows Johan to directly address the needs and frustrations identified by today’s water professionals who require innovative decision support tools. Johan also provides training and technical support to HydroMaster and Datasphere customers and partners.


 

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