During the winter storm last week, the Electric Reliability Council of Texas (ERCOT) saw significant transmission congestion associated with high levels of demand and transmission outages due to wintry precipitation.
One of the most extreme congestion events was on the Stewar_Vertre1_1 constraint near McAllen, Texas, in the Lower Rio Grande Valley.
By Thursday, so much congestion had accumulated on the line that ERCOT declared a maximum shadow price cap due to the irresolvable nature of the constraint. Using Yes Energy’s power market data and solution set, we can sift through the noise and see exactly what caused this major price spike.
A good place to start congestion analysis is Yes Energy’s Constraint Profile tool in PowerSignals® to visualize the nodes and power plants impacted by the congestion via shift factors. Shift factors translate some percentage of a constraint’s shadow prices down to individual nodes based on their ability to exacerbate or relieve congestion by changing their power consumption or generation.
In the case of Stewar_Vertre1_1, there are only two nodes with noticeable shift factors, but both are at 1.00 – meaning every dollar of congestion on the constraint translates to a dollar of higher prices at the node.
Adding in power plant information from the US Energy Information Administration (EIA), we can see that both of those nodes are associated with solar farms – indicating that solar generation output probably plays a role in understanding this congestion.
One of the most common drivers for congestion is a transmission outage. The Outage Constraint Overlap tool lets you search for all transmission outages within a certain distance of a constraint that have overlapped with periods of congestion over a given lookback period.
Using that visualization, we can see that there were six line or transformer equipment outages that overlapped with congestion at Stewar_Vertre1_1 during January 2025.
Source: Yes Energy’s PowerSignals
Of those outages, the Burns_Riohondo1 line has the best temporal lineup with shadow prices on the constraint, but it isn’t a perfect match. For one, the outage schedule shows it starting about an hour after congestion began firing. And for another, the outage was previously out for over a month without any congestion events.
Fortunately, we can use PowerSignals’ Time Series Analysis visualization to understand what other factors might explain that.
The first variable that comes to mind is extreme load given the winter storm, but remember that this congestion primarily impacts two solar farms. We can use the custom formula option to calculate a modified net load variable (subtracting SouthEast solar from WZ_Southern load). Combining that overlay with the transmission outage schedule for Burns_Riohondo1 shows why the outage may have been present for many weeks without causing congestion – the net load levels never got high enough to trigger congestion.
Source: Yes Energy’s PowerSignals
There is still the question though of why we started seeing shadow prices on the constraint before the outage’s published start time from ERCOT?
This is where Yes Energy’s proprietary Live Power® grid monitoring technology can help fill in the gaps. Live Power monitors measure real time flows over transmission lines every 60 seconds and use that information to calculate generation output and load consumption at market moving facilities across the system.
In this case though, the line flows themselves are most useful because Live Power covers the Burns-Rio Hondo 138kV line in question.
Drilling down to five-minute granularity, we can see that Live Power sensors detected a rapid drop in line flows on Burns-RioHondo – indicating a line outage – at 4:15 a.m. on January 21. This was almost 90 minutes before ERCOT would officially report the transmission outage and matches up perfectly with the actual start of congestion on Stewar_Vertre1_1.
Source: Yes Energy’s PowerSignals
Live Power users not only get best-in-class data granularity but also can set up customizable alerts, meaning you could have been alerted to this line outage well before the rest of the market. These alerts let you know when something important is happening with visual cues and even audio alerts in case you don’t have the tool visible on your screen.
For even more alerting functionality, QuickSignals® users can create multi-conditional alerts, so you are only notified when all relevant market conditions are present. In this case, that means rapid line flow changes on Burns-Rio Hondo combined with high net load. QuickSignals alerts can be delivered directly via email or SMS.
If you need visibility into power markets when conditions are at their most extreme, Yes Energy’s data and proprietary solutions set can help you by delivering better direction in a fast-moving environment.
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About the Author: Isaac Lichlyter was a former day-ahead power trader for eight years in CAISO, ERCOT, and PJM. While trading, he used Yes Energy tools, including Yes Energy load forecasts, to diagnose the drivers behind price movement in the market, and now he is helping clients understand how our solutions can meet your needs.