By: Jack Farley, Live Power CEO

When generators commit 100% of their capacity to day-ahead (DA) energy or Ancillary Service (AS) products, they forfeit the margin opportunity from real-time (RT) prices spikes. Conversely, when generators reserve capacity for the RT market they run the risk that RT prices clear at a lower level than DA prices. This price uncertainty is the key challenge in determining the revenue-maximizing unit commitment - do you hold back capacity or commit it all to DA

On Thursday, November 11th in SPP there were significant real-time (RT) price spikes in the morning and evening peak hours. Several factors conspired to produce price spikes over $1500, including forecast errors, ancillary service limits, scarcity pricing structures, and relatively soft day-ahead (DA) prices. We will examine these factors and ask one important question. Were there signals to provide early warning of these issues?

Continued development of wind generation throughout MISO presents interesting challenges when reviewing market dynamics. Knowing how specific resources are reacting to different market signals at an operational level is made possible with real-time generation data from our partner Live Power alongside market data in Yes Energy. Having all of this data in one place will continue to be important as MISO market congestion remains active and persistent around areas of heavy wind development.

Summertime market volatility is in full force in ERCOT and in this Market Driver Alert, we break down a particularly volatile day on July 7th. Demand was high when supply was low, leading to scarcity price adders going into effect and the locational marginal price (LMP) at Hub North spiking to over $900. In this blog post, we will use a combination of market data from ERCOT and generation data from our partner Live Power in various Yes Energy products (PowerSignals, QuickSignals, DataSignals) to analyze what led to these market conditions.

In this Market Driver Alert, we break down a perfect storm of market conditions that led to system-wide price volatility in MISO on 5/22. We’ll walk you through how market data in Yes Energy alongside real-time generation data from our partner Live Power helped explain why prices spiked to over $2,300/MWh throughout the entire MISO footprint.

In this market driver alert, we will dive into 4/5/21, which was an eventful day in ERCOT. We will break down what could have led to Hub North spiking to $2,276 and why wind generation may have had something to do with it. In this blog post, we will leverage market data in Yes Energy, alongside 60-second generation data from Live Power and generation outage data from IIR Energy.

By now most of the world knows about the cold snap in ERCOT the week of 2/15/21 (if not, check out our blog post here), but do you know the generation side of the story? You may know some of the story from watching the news, like we have - including claims that it was a wind issue or a natural gas supply issue.

Throughout the week of 11/2/20 there were many transmission constraints that bound throughout MISO, which contributed to price spikes throughout the entire ISO. On multiple occasions the real-time (RT) LMP at Indiana Hub exceeded $100, with rippling price impacts throughout the ISO. In this Market Driver Alert we do a deep dive of why Yes Energy customers who subscribe to both Live Power and IIR Energy had more insight into what led to this price volatility. 

What contributed to the congestion and price spikes throughout MISO the week of 11/2? As you can see below, there were many transmission constraints binding at the same time as generation outages. In the screenshot below, the yellow circles/lines are transmission constraints reported by MISO and the red/black icons are generation outages reported by our partner IIR Energy.

Let’s hone in on one constraint in particular that bound multiple times the week of 11/2, and that’s the Fort Smith constraint. As you can see below, there were many generation outages in the area that were reported by our partner IIR. A few of the outages, like Arkansas One and Hot Spring, had recently started, which could have contributed to the Fort Smith constraint binding the week of 11/2.

Why are these outages a problem for the Fort Smith constraint? Because many of the generators that were on outage the week of 11/2/20 have a positive shift factor relative to the Fort Smith constraint, meaning that by generating they help alleviate the constraint. For example, Arkansas One, White Bluff, and Hot Spring all had reported outages the week of 11/2 and they all have high positive shift factors relative to the constraint, meaning that they are unable to respond to the Fort Smith constraint by ramping up, thus exacerbating congestion in the area.

Generation data from our partner Live Power for Arkansas One, Hot Spring, and White Bluff confirmed that these plants were not operating at their full capacity on 11/2/20, which aligns with outage information reported by IIR. So which plants stepped up when these plants couldn’t because they were on outage?  

Cottonwood is another plant monitored by Live Power that has a high positive shift factor relative to the Fort Smith constraint. Did it step up when Arkansas One, Hot Spring, and White Bluff couldn’t? As seen below, Cottonwood (blue line) ramped up in response to the Fort Smith constraint (red line) as we would expect. The 60 second generation data from Live Power for this plant shows that on multiple occasions on 11/2, 11/3, and 11/4 Cottonwood ramped up in response to price spikes at Indiana Hub (green line) that were likely a result of the Fort Smith transmission constraint.

In summary, generation data from Live Power and IIR data, alongside Yes Energy market data helps traders understand the impact of generation outages on transmission constraints. Using shift factor data in Yes Energy, traders know which generators have leverage over a constraint and using 60 second generation data from Live Power they know which plants actually respond when prices are spiking. This allows traders to be better prepared in the future when similar market conditions occur.

In this blog post we’ll dive into what happens when load comes in higher than forecasted in PJM and why having data from Yes Energy and Live Power can make or break a trade.