Leveraging Clir’s risk framework

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Clir Risk assessment framework

Asset health

Quantifying turbine health through operational data.

  • Meteorological loading
  • Operational loading
  • Existing health issues
  • Natural catastrophe risk

Asset reliability

Quantifying reliability and failure risk.

  • Mean failure rate
  • Mean repair time 
  • Major failure frequency and claim history
  • Known wind turbine issues

Operational practices

Assessing and supporting the highest standards of O&M.

  • Drivetrain inspection and monitoring
  • Blade inspection and monitoring
  • Major component replacement
  • Storm preparedness
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Contractual risk

Assessing contractual coverage and claim impact.

  • Warranty 
  • Service agreement
  • Major maintenance budget
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Asset health

The health of an asset can have a significant bearing on project performance and asset valuations as well as insurance and financing costs. Delving deeper into operational indicators and comparing with Clir’s global dataset provides clients and partners with a clearer picture of asset risks. Asset health indicators analyzed include meteorological loading, operational loading and component health.

Asset reliability

Statistics such as failure rate and repair time are often used to evaluate the reliability of equipment and effectiveness of operations and maintenance practices. Quantifying these metrics at a site specific level, using SCADA data, and comparing them to Clir’s global dataset provides an indicator for the farm’s global reliability rank.

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How we support clients with risk reduction

Clir’s risk assessment contains a comprehensive list of the top insurable events, along with a set of recommended mitigations. Clir Risk evaluates the mitigation options available and recommends the most cost efficient option.

Clir’s team works to quantify the risk reduction benefit so that the client can make an informed decision about whether to mitigate the risk. Our team has extensive experience working with operations, site and OEM teams, supporting our clients’ risk mitigation implementations.

A theoretical example of risk reduction in practice:

Category

Natural catastrophe (lightning) and attrition loss (blades)

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Mitigation evaluation

Enhanced inspection regime to sooner identify damage before it turns catastrophic and to verify lightning protection integrity

  • Adjust inspection schedule according to conditions.
  • Drone inspections rather than ground-mounted.
  • Expand scope to include internal inspections and targeted inspection of the earthing system and lightning monitoring system in accordance with applicable IEC standards.

Aftermarket lightning card strike system to increase the proportion of strikes covered by OEM rather than insurance.

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Data used

O&M survey responses, quarterly verification of approach with photographs/logs and industry benchmarks.

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Clir’s guided mitigation

  • A small fee was paid to have the O&M provider adjust the frequency and method of inspection
  • The contract was renegotiated at renewal to up the frequency of inspections
  • An independent third party was brought in for verification

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Validation

Standardized risk rank was reduced once a new inspection regime was in place.

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Value

The farm reliability increased and the risk reduction was considered by insurers on renewal.

Clir Risk and GCube Smart Insurance

Clir Risk powers GCube Smart Insurance by radically improving the accuracy of insurance risk assessments. Using intelligence from 200 GW of claims data, the partnership enables superior renewable energy insurance coverage and faster claim handling.

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01

Month one through four

Client data is onboarded onto Clir Portfolio and a baseline Clir Risk assessment is performed.

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02

Months six through nine

Clir works with the customer to evaluate and implement risk mitigation options.

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03

Month 10

Final risk assessment is produced.

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04

Months 11 and 12

Customer renews insurance, leveraging the risk assessment for improved terms.

Learn more about our endorsed risk framework.

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