Machine learning-powered modelling of production shape and volume provides improved certainty when compared to industry-standard linear regression.
Offtake and hedge optimization
Hourly settlement presents a considerable financial risk to owners when factors impacting production shape and volume, such as the variability in intra-day energy production, are not properly considered.
By using modelled hourly resource to review each month-hour pair, Clir provides valuable insight into the suitability of hedge values. Layering market intelligence on loss factor variability across the industry enables values to be further tuned for technology and asset location.
This analysis enables owners to assess the likelihood of a project failing to meet the hedged quantity at any given hour. It also offers the ability for owners to simulate the hedge settlement for any chosen value.
The volume model can be used to calculate the uncertainty in expected generation over different return periods for business interruption insurance. This also supports the sizing of business interruption risk exposure to ensure coverage and risk management are optimal.
Estimate lost energy during outages
The probabilistic hourly resource distribution can be used to optimize outage planning and estimate lost energy during planned or unplanned farm-wide outages.