In this Market Driver Alert, we break down a recent wind driven constraint in ERCOT using 60 second wind generation data from our partner Live Power so you can be prepared before market volatility hits this summer. We’ll walk you through how to identify wind driven constraints, what impacts they can have on price, and how other generators respond to make up the difference.
Let’s dig into the SANMIGL 345KV SANMIGL_ATAH constraint, which has bound for over 8 hours in the last month and reached max shadow prices of over $2,000. Using the Constraint Summary module in Yes Energy, we can see that this appears to be a wind-driven constraint. You can tell that by coloring the shift factors in the bottom right chart by Wind Farms, which means any blue dot is a price node associated with a wind farm. A blue dot in the top right corner has a high positive shift factor relative to this constraint, meaning if it’s a generator node then by generating it helps alleviate the constraint. Conversely, dots in the bottom left have high negative shift factors relative to the constraint, meaning ramping down generation helps alleviate the constraint. As you can see from the cluster of blue dots in the top right corner, there are many wind farms with high positive shift factors, meaning they can reduce congestion by generating. As you can see in the price node table in the bottom left, Live Power monitors many of these wind farms.
Source: Constraint Summary module in Yes Energy. Click picture to enlarge.
Due to the high positive shift factors associated with the wind farms impacted by this constraint, this tells us that if the wind is not blowing, there is a higher likelihood of this constraint binding. Let’s explore that theory deeper. The chart below shows that the constraint hits around 12 pm CT on both 6/23 and 6/24, which coincides with when wind generation in ERCOT is low (blue line, using data from Live Power monitored wind facilities). In the graph below, the primary y-axis is generation (MW) and the secondary y-axis is the shadow price associated with the constraint. The impact on hub prices (yellow line) is on a hidden axis. As you can see below, when the constraints hits, the RT LMP price at Hub South immediately spikes. This is what we would expect to occur based on the leverage that we saw wind has over this constraint in the Constraint Summary module. Low wind generation during peak load makes the constraint worse, thus increasing prices. f
Source: Time Series Analysis module in Yes Energy. Click picture to enlarge.
What do generators in the area do when the constraint hits due to wind generation being low? Do any generators ramp up to meet demand? To start to answer that question, let’s use the Constraint Profile module to identify days in the past that were particularly volatile for this constraint. This module allows us to drill into a particular constraint so we can identify trends for what leads to this constraint binding. It also allows us to filter for things like shadow price so we can identify days in the past that had high shadow prices due to the constraint binding.
If we look at the behavior of this constraint from 6/1/20 to 7/10/20 and filter for when shadow prices are particularly high, we can see in the table below that this constraint reached shadow prices of over $2,000 on 6/24. The table shows the date/timestamp for all of the instances this constraint bound over this time period and is filtered for when shadow prices are > $500 because we clicked on the > 500 bar in the first histogram. The three bar charts are histograms that bucket the instances that the constraint bound for that particular category. For example, the bottom histogram is showing the instances that the constraint bound over specific intervals of wind generation when shadow prices were > $500. This is an aggregate data series from Live Power for all of the wind facilities they monitor in ERCOT. As you can see, when this constraint binds, wind generation is low, which is what we would expect based on what we saw in the Constraint Summary module, which showed that many of the wind facilities in ERCOT South have high positive shift factors relative to this constraint.
Source: Constraint Profile module in Yes Energy. Click picture to enlarge.
Let’s dig into 6/24 to see what the topology of the grid was at this time. Which generators ramped up to meet the demand when wind generation was low? We can explore that question by drilling to the Analytic Price Map module from the date/timestamp of interest in the table on the right.
Source: Constraint Profile module in Yes Energy. Click picture to enlarge.
On 6/24 at 11:30 am CT (i.e., HE 12:30) the SANMIGL 345KV SANMIGL_ATAH transmission constraint (the yellow circle on the map) hits. During that time you can see that wind generation in ERCOT South is low (red plant icons equate to low capacity factors). If we toggle through the 5 minute intervals after the constraint hits we can see how generators in the area respond. Note how the capacity factor of Coleto Creek is at 89% when the constraint hits at 11:30 am.
Source: Analytic Price Map module in Yes Energy. Click picture to enlarge.
If we toggle forward to 11:40 am CT (i.e., HE 12:40), when the shadow price associated with the constraint hits its peak of $2,417, we can see that Coleto Creek ramps up to a 94% capacity factor. It seems that the generator may have been ramping up to help meet this demand. We can infer that because when the constraint alleviates around 1 pm CT, we see the capacity factor of Coleto Creek ramp down to ~90%.
Source: Analytic Price Map module in Yes Energy. Click picture to enlarge.
So what could you do with this information to be better prepared in the future? You could set up a multi-condition alert in our low-latency dashboard product, QuickSignals, based on the aggregation of Live Power monitored wind generation in ERCOT and changes in price at Hub South. When the conditions are met you could get an audio alert, text alert, and/or e-mail so you can quickly respond before price volatility hits.
Source: QuickSignals module in Yes Energy. Click picture to enlarge.
In summary, Live Power data, alongside Yes Energy market data (constraints, shift factors, and prices) helps you understand the impact of wind-driven constraints on market prices, as well as understand how plants in the surrounding area respond when wind generation is low. This allows you to be better prepared in the future when similar market events occur.