We know who is responsible for electric grid reliability in wholesale markets during the energy transition; ISO’s. This means the ISO’s must decide what is needed to ensure reliability of the electric grid each hour of the operating day over a capacity commitment period and the ISO will be held accountable for failures when reliability falters. We saw this in Texas with ERCOT.
But the ISO’s are dependent on many parties that play roles in the grid, which they have no direct control over, i.e. Natural Gas suppliers, transporters and producers, and other factors, i.e., impacts from weather events. This introduces risk to reliability which someone owns. Is the ISO accountable when a fleet of natural gas generating units are unable to acquire fuel due to extreme weather events, like Storm Uri in Texas, or when a blizzard covers solar panels for a week? "Texas’ gas supply remains vulnerable to extreme weather — just last December, during Winter Storm Elliott, gas output fell 32% and more than 25,000 megawatts — one-third — of thermal power plants were offline at some point during the three days of Elliott, even though there was no snow and ice."
Who owns the risk?
Does the use of ELCC or MRI provide an answer to who owns the risk?
ISO’s use ELCC or MRI to accredit capacity resources to indicate the percentage of their nameplate capacity that can be counted on to deliver when called upon to generate energy. ISO’s use these formulas to forecast the amount of capacity they can reliably count on to contribute to the total capacity amount they believe is needed to meet peak demand and ensure a reliable electric grid. In theory a solar resource with an ELCC value of .25 means that 25% of a resource nameplate capacity MW is used to calculate the “forecasted” capacity contribution of a resource. So a 100 MW solar resource with a .25 ELCC is expected to contribute 25MW toward capacity reliability requirements. If an ISO determines that 100 MW of capacity is needed for reliability this would require 4 solar resources, each contributing their 25 ELCC MW, to satisfy reliability requirements. In this case the ISO would issue capacity payments to the 4 resources for 25MW each at the capacity clearing price. But this design is deeply flawed.
Solar resources produce energy at their nameplate capacity MW when conditions are right; the sun is shining brightly, at the right angle, during cool temperatures. April is a highly productive period for solar production of electricity; December, not so much. Using a static ELCC value to calculate forecasted solar capacity contributions is guaranteed to be wrong most hours during a commitment period. There are other dynamic factors that impact “Expected Operational Efficiency” (EOE) which a static ELCC value fail to accommodate, i.e., age of solar panels, solar panel implementation (static of rotating), inverter settings, inverter technologies, etc.
What is the alternative to ELCC and MRI?
Let generators place offers for capacity into a capacity exchange, on an hourly basis, stating the amount of capacity MW they are willing to commit to over the course of a commitment period. This gives the ISO a more accurate estimate of the capacity MW that can be expected to be available throughout the year, based on the “ground truth” knowledge that the generator operators have about their resource’s performance characteristics. This approach gives Generator operators more freedom and control to apply their own risk assessment algorithm (risk appetite, risk threshold, etc.) to decide how much capacity to commit to providing, knowing the risks that could result in pay for performance penalties if they fail to perform. Generators have control over their own risk using this approach. This also gives the ISO a more accurate count of the capacity MW’s that can be expected to be available when determining the amount of capacity needed to ensure reliability, during each hour of the operating day over a commitment period. Using this information, along with load forecasting tools, an ISO is able to determine the peak load requirement when deciding the total amount of capacity needed, per grid service type, to meet peak demand for each hour of a commitment period. This approach squarely places the accuracy for capacity offers on generator owners and the risk associated with capacity commitments on the generator owners while the risks of overall reliability and the need to acquire adequate grid services capacity each hour of the operating day to meet demand remain with the ISO.