Are you looking to analyze participant positions in the financial transmission rights (FTR) markets? Do you want to benchmark competitors?
A detailed FTR analysis and benchmarking of competitors in the PJM Interconnection (PJM) and Midcontinent Independent System Operator (MISO) (among other grid operators) involves understanding the intricacies of FTR markets and conducting a thorough evaluation of how your competitors perform and operate within these markets.
Here’s a step-by-step guide on how to approach this.
FTRs are financial instruments that allow holders to hedge against (or speculate on) transmission congestion costs between two points on the electricity grid. They pay out based on the difference between auction clearing price and day-ahead market congestion component price for the path defined.
PJM and MISO are two of the major grid operators that offer FTRs, and their markets operate differently in terms of auction structure, grid congestion patterns, and market rules.
In this blog, you’ll see how to do the following:
All of these will help you better inform yourself of competitors’ trading activities and improve your trading strategies.
You need to start with collecting detailed historical FTR auction data from the markets, such as PJM and MISO.
This includes:
Below is an example of this type of data that shows the volume over time of top industry players in PJM, comparing those values to Greenhat’s volume over time.
Source: Yes Energy’s FTR Positions Dataset
Begin by examining the historical auction prices for the specific FTR paths that your competitors are trading. Compare how prices fluctuated based on congestion, demand, and generation patterns.
Then analyze the profitability of FTR positions by comparing the auction price of the FTR against the actual congestion payments received. This will help assess whether your competitors are consistently profiting from their FTR positions.
Below is an example of analyzing the top players in a specific ISO by mark-to-market (MtM) values.
Source: Yes Energy’s FTR Positions Dataset
Lastly, study congestion data across the PJM and MISO networks to understand how congestion impacts specific paths and competitors’ FTR positions. Identify which paths are most congested, and how this affects the financial outcomes of FTR positions.
Now that you have historical data collected and analyzed, identify which paths your competitors focus on. For example, are they targeting high-congestion areas? Focusing on less congested routes where there might be less competition but more stable returns?
You will want to analyze the frequency and scale of your competitors’ participation in FTR auctions. Are they aggressive in obtaining long-term FTRs or prefer short-term opportunities?
It is also key to determine whether your competitors diversify their FTR portfolios across different locations and time frames or they concentrate on specific zones.
Determining how your competitors perform relative to peers is important. Determine your competitors’ market share in terms of FTR auction awards and comparing it to their performance is going to identify are they just a large players in the market, or are they actually performing better than peers on a volume-adjusted basis.
This should include benchmarking competitors based on their return on investment (ROI) for FTRs. An example is looking at historical performance metrics like FTR auction spending (cost) versus congestion revenues earned.
Risk-adjusted returns are also important to analyze. You can do this by evaluating the volatility of the paths they select relative to risk used. Higher-risk paths may offer larger returns but can also cause significant losses if congestion doesn’t occur as expected.
Then, look at long-term versus short-term FTRs. Competitors may differ in their approach to securing long-term FTRs (which offer stability but require accurate forecasting of future grid conditions) versus short-term FTRs (which may be more volatile but offer higher returns in highly congested periods).
Finally, observe auction participation timing. Some competitors may focus on the annual FTR auction, while others might prioritize monthly or seasonal auctions. Benchmarking competitors based on their auction timing can provide insights into their strategies.
Then, model different congestion scenarios to predict future FTR performance. You can base these scenarios on forecasted load growth, new generating resources coming online, transmission upgrades, or changes in generation mix (such as increased renewable energy integration).
For example, ISO-published power flow topologies can be used to model future congestion, and precise information on upcoming transmission upgrades, new generators, or data center operations to analyze how that may impact congestion in future periods. To learn more about how FTR Traders are using this type of data around changing infrastructure, see our blog: Leveraging Our Infrastructure Insights Dataset in FTR Trading.
Geospatial analysis can also be performed by integrating FTR Positions Dataset with Geo Data to review concentration risk as well as calculate potential losses with the risk metrics of value-at-risk (VaR) and stress (worst case) based on historical simulation models that can be fully customized and tailored per your requirements. To learn more about how FTR Traders are using this type of data around concentration risk and risk metrics, see our blog: Using Geo Data to Analyze FTR Risk.
Source: Yes Energy’s FTR Positions Dataset & Geo Data
Source: Yes Energy’s FTR Positions Dataset & Geo Data
Use scenarios like these to test how sensitive your competitors’ FTR positions are to changes in grid congestion patterns. This helps assess their risk exposure and potential vulnerabilities.
Integral to this type of analysis is ensuring you are watching any regulatory or market rule changes in the markets that may affect FTR trading. Changes to auction rules, transmission planning, or congestion pricing can significantly impact FTR strategies. You can keep an eye on these through the stakeholder processes at the grid operators and/or through a number of vendors or attorneys.
Assess how these regulatory changes might affect your competitors’ positions or strategies. For example, a change in how transmission upgrades are handled could impact the profitability of certain FTR paths.
Finally, summarize your findings on how competitors operate in the PJM and MISO FTR markets. Highlight key differences in their approaches, such as path selection, risk tolerance, and auction behavior.
Present a comparative analysis of competitors’ FTR performance, focusing on metrics such as market share, profitability, and portfolio diversification.
Provide actionable insights on how your company can adjust its FTR strategies to stay competitive or gain an edge in the market. This might include recommendations on which paths to target, auction participation timing, or risk management tactics.
Yes Energy’s FTR Positions Dataset solution provides FTR trading organizations with unprecedented visibility into FTR market positions.
Historically, only FTR trading organizations with large IT budgets have been able to build systems to gain visibility into the positions, performance, and risk of their competitors in the market. With FTR Positions Dataset, you can outsource this expensive data management, including trade capture, model remappings, and ISO changes.
We deliver all of this on the powerful Snowflake cloud platform. (Snowflake is a data warehouse available across multiple cloud regions). This allows you to answer the above questions in seconds, compared to a more manual process that may take hours or days for each auction. You can also further integrate this data with Yes Energy’s DataSignalsTM Cloud datasets, internal data, and other third-party data available on Snowflake, fueling powerful big data analysis.
Learn more about the FTR Positions Dataset today, or schedule a demo!