Winter Storm Fern pushed cold temperatures across a wide stretch of the U.S., and power markets responded with sharp volatility. Price spikes appeared in multiple regions during the tightest hours, while gas conditions also showed signs of stress in key areas. In the aftermath of Fern, it is useful to see what these events reveal about where the system remains most sensitive when demand surges and fuel and operational flexibility get tested.
What happened across major markets
Across several ISOs, the pattern was consistent: peak demand windows created the most pressure, while changing renewable output and fuel availability shaped how each region performed.
-
ERCOT saw brief price spikes around morning and evening peaks, while strong midday solar production helped keep prices lower during the middle of the day.
-
PJM experienced sharp real-time volatility during evening peak conditions when demand lined up with weaker renewable contribution.
-
NYISO showed volatility when real-time load ran above forecast, calling higher-cost generation online, while wind and hydro later helped moderate the evening period.
-
ISO New England faced particularly tight conditions with a heavier reliance on fossil generation during the highest-stress hours, including periods where oil played a meaningful role in the mix.
-
MISO saw sustained stress in parts of the system, with regional separation and operational constraints showing up as persistent high pricing in some zones.
The takeaway is simple: cold events compress optionality. When load rises quickly, the system depends on what can ramp, what fuel is available, and how reliably supply can meet peak conditions.
Why prices moved
Three drivers explain most of what was seen during Fern:
1) Peak-hour demand pressure
Cold-driven load concentrates stress into a few critical windows. Morning and evening peaks saw the strongest overall real-time volatility.
2) Renewables timing and variability
Renewables can materially reduce stress during the hours they are present, but tighter conditions can emerge as output tapers. Several markets showed this pattern during Fern, especially around evening peaks when solar generation began to peel off at the end of daylight hours.
3) Fuel availability and fuel switching
When gas deliverability becomes tight, regions may rely more heavily on higher-cost fuels. That dynamic is most visible in places like New England during cold snaps, where the generation stack can shift quickly under stress.
On the gas side, a drop in the pipeline sample and elevated spot pricing signaled tight sourcing during the event and point to constrained conditions that can coincide with peak-hour power volatility. Much of the U.S. experienced a shortage of natural gas, which can play a large role in power price volatility. The exact causes can vary by region, so it is better to focus on observable outcomes: tighter gas conditions and the resulting pressure on power markets.
A useful lens: Northern Virginia and the data center corridor
One region stands out as a strong case study for resilience planning: Northern Virginia, where dense clusters of data centers create a large, always-on load footprint.
This is a useful lens because it forces a practical question: when cold weather tightens the system, where do high-load clusters intersect with the surrounding energy infrastructure, and where does market stress show up most clearly?
By bringing together the following three elements, the picture becomes clearer:
-
Data center locations (the load cluster)
-
Nearby gas pipeline infrastructure (infrastructure context and proxy for fuel access pathways)
-
Power pricing nodes (where stress shows up in market signals)
Key Takeaways
Winter Storm Fern reinforces a straightforward idea:
Extreme volatility tends to concentrate where peak demand meets limited flexibility, especially in regions with dense, always-on load.
For market-focused teams and infrastructure planners, the value is in the ability to quickly locate where stress concentrated and to prioritize where deeper analysis should focus.
Practical questions to ask next:
-
Which pricing nodes and corridors showed the sharpest stress during peak hours?
-
How concentrated is the load near those stress points?
- What does nearby gas infrastructure context look like around those load clusters?
-
Which areas merit deeper, site-specific resilience planning and operational review?
Cold events will keep happening. The teams that prepare best are the ones that can identify where the system is most exposed, and focus their analysis and planning accordingly.
How to use this approach
An integrated infrastructure view that brings together load clusters, energy infrastructure context, and market stress points can help teams prioritize where to investigate further, whether the goal is operational preparedness, regional risk assessment, or long-term infrastructure planning.
