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Renewable energy risk management: Risk Engineering and insurance

06/02/2022 · 4 minute read

The increased frequency and severity of extreme weather events, and the devastation they cause, is top of mind for many organisations. For renewable energy companies, the potential destruction following a storm often translates to higher insurance costs at a time when coverage premiums are already increasing.

The potential for damage is often leading companies to make overly conservative risk estimates to ensure sufficient protection. This means, however, that many renewable energy organisations may be purchasing unnecessary insurance coverage at the expense of investments in their projects.

But newer modelling techniques that take into consideration additional variables are providing renewable energy companies with more accurate and higher confidence risk estimates — and empowering them to achieve substantial cost savings.

Single-location risk models lack accuracy

Risk modelling for renewable energy properties, such as wind or solar farms, has traditionally taken into consideration the location of the insurable entity. But models are rarely able to account for the large areas covered by a single operation. Further, traditional models often base their estimates exclusively on location without considering other attributes that could affect a structure’s resilience during a storm.

Let’s take the example of a solar farm that spans over 40 hectares in an area prone to convective storms. A traditional model will consider the likelihood that the solar farm is hit by a hailstorm and estimate the potential damage, often in the tens of millions of dollars.

But the storm’s intensity is unlikely to be uniform across the large area. While some solar panels may be damaged by hail, others may be completely unscathed.

Similarly, a flood may not lead to the same water elevations across a large insured property, with some areas experiencing water damage and others left completely dry.

Single-location risk models tend to provide an all-or-nothing result that may not reflect a property’s real exposure. Concern around lack of accuracy often leads risk managers of renewable energy companies to err on the side of caution and purchase additional coverage.

Increased certainty, cost savings through new risk modelling techniques

Newer, more granular modelling techniques can look at aggregate locations as well as engineering information, such as the type of property and construction material, occupancy, layout, and elevation. Engineering information allows for more accurate risk estimates based on the main exposures of different property types. Hail, for example, is likely to impact a solar farm more prominently than a wind farm, while lightning is generally more problematic for wind farms. Windstorms and flooding may also affect solar and wind farms differently, leading to more accurate information when models are run for each peril.

Often, these newer models show credible exposure reductions in the range of 25% to 35% for rare weather events that can have a very big impact, although some companies have seen their exposure go down by up to 60%. At times, the models reveal that a company’s exposure is below the primary insurance limit and remove the need to purchase excess coverage or extra limits, leading to substantial savings.

Although rare, there is the potential that more precise modelling will instead uncover a higher exposure for companies. While this would require increased insurance coverage and translate into additional costs, renewable energy organisations in this position can still benefit from increased certainty that they are purchasing the right amount of coverage.

More accurate modelling allows for better risk mitigation

With more accurate information in hand, risk managers can not only negotiate insurance terms with greater confidence but also enact important risk mitigation measures.

Renewable energy technologies are experiencing accelerated growth and profound change. Designs and installed components are evolving rapidly. In some cases, those changes may introduce new risks and in others they may prevent them.

Aside from gaining greater clarity and more accurate estimates to help risk professionals purchase the most appropriate insurance coverage, sophisticated energy risk engineering solutions can support your:

  • Risk mitigation and control: Applying best practices on loss control measures can reduce the frequency and severity of outages or losses. 
  • Reduction of the cost of risk: Accurate risk evaluations and loss modelling supports companies’ risk mitigation and retention strategies, helping risk managers make the best risk transfer choices. 

As the industry matures, renewable energy companies can benefit greatly from implementing advanced risk engineering strategies to not only better manage hazard exposures, but also to confidently invest in their project’s future.

This website and any recommendations, analysis, or advice provided by Marsh (collectively, the ‘Marsh Analysis’) are not intended to be taken as advice regarding any individual situation and should not be relied upon as such. Any modelling, analytics, or projections are subject to inherent uncertainty, and the Marsh Analysis could be materially affected if any underlying assumptions, conditions, information, or factors are inaccurate or incomplete or should change. The information contained herein is based on sources we believe reliable, but we make no representation or warranty as to its accuracy. Marsh makes no assurances regarding the availability, cost, or terms of insurance coverage.

LCPA: 21/206

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