The Power of FTR Auction Constraint Data
by Jake Landis
Financial transmission rights (FTRs) are complex financial power products. [Read more about different financial power products]. Given the nature of these products, market participants participating in these markets need to have a comprehensive understanding of the grid’s components and the variables that can drive pricing.
One critical puzzle piece needed to understand these complex financial energy market instruments is FTR auction constraint data. FTR auction constraint data, alongside other fundamental market data, allows participants to reference auction constraints and associated auction clearing prices geographically, completing the puzzle when it comes to auction results.
Below is a visualization of nodal auction clearing price data and corresponding auction constraints (purple items located on constrained transmission lines/equipment). The magnitude or shadow price of these constraints on FTR auction clearing prices can also be seen.
Using Yes Energy’s solutions, including our integrated FTR Constraint Data, we can examine clearing prices over time from various market auctions. Below, we can see that historically, auction clearing prices resulted from a congested path, but when the actual settlement month occurred, the congestion was reduced, and even became a positive value
Why didn’t auction values materialize as forecast from previous auction results? Continuing the investigation into a particular FTR auction (January monthly auction in this example), one analysis looks at what actually occurred during the month.
In the next image, we can analyze what types of system conditions were in place and how those compare to the auction results. This provides an opportunity to see any congestion changes between the auction and actual results, and how those changes were reflected in the final settlement of prices.
In the image below, we have our original auction constraints and have now overlaid actual transmission constraints (in yellow) alongside transmission outage data (in red) and the results of the analysis in profit/loss margins for the nodal price locations. What this specific example illustrates is that the actual settlement month had far fewer constraints than the constrained grid that was anticipated when the auction occurred.
Another powerful use of auction constraint data, particularly georeferenced data, is the ability to observe auction changes over time. Beyond the changes for mark-to-market calculations, we can observe and analyze specific auction constraints over time. Has congestion shifted from one auction to the next? Has the transmission outage landscape changed?
In the below example, four sets of auction constraints are displayed for a single settlement month, providing historical auction data overlaid in one image. From this analysis we can examine the changes to congestion, overlay transmission data if desired, and observe both past and future FTR auction data.
FTR Constraint Data is a powerful dataset that helps FTR market participants perform a comprehensive analysis of the markets and visualize the impact of constraints to better inform their trading strategies.