Satellite-based Tornado Cover for Solar Farms

Full Case Study

Satellite-based Tornado Cover for Solar Farms

Product details

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Risk covered

Tornado Risk starting from EF0

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Client profile

Utility-scale Solar Farms >10MW

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Insured location

Texas, United States

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Index

Based on % of damaged surface

PAYOUT STRUCTURE

Based on % of damaged surface 

Total Insured value: 200M USD

Limit: 25M USD

  • Trigger 1: NOAA (even EF0)
  • Trigger 2: Damage detection by satellite 

Payout depends on percentage of surface affected and the limit: 

  • 15% of the site being affected
  • The insured receives 3,750,000 USD

case study example

The construction and operation of solar farms has been booming, especially in the Mid-West and South-West of the United States. Unfortunately, severe convective storms, including tornadoes, threaten operationality and financial stability of those investments. With solar farms becoming larger and more expensive, the need for insurance grows amidst the widening protection gap.

Problem

A solar farm owner reached out to Descartes after being affected by a weak EF-1 Tornado. They were unable to obtain traditional insurance cover any longer. Whilst our typical parametric tornado product - based on EF scale only - is well-suited for large structural buildings in urban areas, it shows limits for solar farms, which are low-rise assets in remote areas. As a result, the modelled payouts of the EF scale parametric product could not match the historical loss of the client and would have left them underinsured. That’s why Descartes developed a new custom product for solar farms.

Solution

The alternative is a satellite-based tornado cover powered by very high-resolution imagery, utilizing the tornado track as first trigger and an area index based on the percentage of damaged surface to determine the payout. Were this client insured with Descartes, it would have resulted in adequate parametric payouts at an optimized premium. This approach brings a very high correlation between damage on the ground and the modelled payouts, effectively reducing the basis risk.

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