What Causes Power Outages

Ask most people what causes power outages and they’ll say storms — hurricanes, ice, lightning. It’s the obvious answer, and it’s incomplete. A large 2023 dataset of public power utilities tells a different story: the cause that dominates the news is not the cause that triggers the most outages day to day. Trees, aging equipment, and animals — overwhelmingly squirrels — each produced more individual outage events than storms did. Understanding why requires splitting one question into two, and they don’t have the same answer.

The two questions are: what causes outages most often, and what causes the most damage when it does. Conflate them and every source you read will seem to contradict every other. Keep them separate and the picture snaps into focus.

Frequency vs. Impact: Why the Numbers Seem to Disagree

A 2023 study covering more than 320 U.S. public power utilities tracked roughly 73,700 sustained outage events across 5.3 million customers. When ranked by the sheer number of outage events, the results look like this:

These are measured event counts from a single, clearly scoped dataset — public power utilities only, one year, one country. They don’t represent all U.S. utilities; investor-owned utilities aren’t in this picture. Keep that scope in mind before generalizing.

What the table shows is that no cause runs away with the lead. Trees top the list, but by a margin thinner than you’d expect — equipment failure is right behind, squirrels close after that, and storms rank fourth. The “top cause” question is, in event-count terms, genuinely tight.

But here’s the tension: backup power vendors and utilities consistently describe weather as the leading driver of outages. They’re not wrong — they’re just measuring something different. A single major storm can knock out power to hundreds of thousands of customers for days. One squirrel shorts a transformer on a residential block for two hours. When you rank by total outage minutes or by customers affected per event, weather moves decisively to the front. Both framings are accurate. They answer different questions, and which one matters to you depends on whether you’re managing a distribution network or deciding whether to buy a backup generator.

It’s worth noting that vendors selling backup power, and utilities explaining service interruptions, both have reasons to emphasize dramatic weather events. That doesn’t make them wrong — storms genuinely dominate severity metrics — but it’s worth treating the framing with a light touch of skepticism when the source profits from your concern about blackouts.

The Squirrel Problem (and What It Actually Tells You)

Squirrels cause around 7,200 outage events a year in this dataset. In one region, they were the single top cause, responsible for roughly 19% of all outages recorded there. That’s not a quirky footnote — it’s a real operational problem for utilities managing overhead equipment.

You may have seen the claim that animals cause 11% of all outages. Treat that as a popular rule of thumb, not a finding — it circulates without any stated scope, year, or methodology. The measured 2023 figure gives you something more useful: a concrete event count, with a defined population and a single year, rather than a bare percentage with no home.

The broader animal story is about what squirrels represent structurally. Rodents and birds find their way into substations and onto lines, contact two conductors or a conductor and a ground, and trip a breaker. The outage is local, usually brief, and extremely repeatable. A utility in a heavily wooded suburban area can log dozens of these a month — none of them dramatic, all of them adding up. The share is also seasonal; rodent activity peaks in warmer months, which is one reason the 2023 data shows nearly 35% of all outages occurring in June through August (storm season and rodent season overlap considerably).

Where You Live Changes the Answer

One of the most important things the 2023 regional data shows is that there is no universal “top cause.” The national totals smooth over real regional variation, and your local reality can look quite different from the aggregate:

• Region 2: Storms led, accounting for about 24.5% of outages
• Region 3: Squirrels led, at about 19.2%
• Region 7: Trees led, at about 14.8%

Notice that even the top cause in each region captures only a modest share — between roughly 15% and 25%. No single cause dominates even locally. Climate, tree canopy, and wildlife population all interact to shape the mix, which means a resident in a storm-prone coastal area faces a genuinely different risk profile than one in a heavily forested inland suburb.

Reporting a single national “most common cause” erases this structure entirely and hands you the wrong mental model for your own situation. If you’re trying to understand your own outage exposure — for preparedness planning or just curiosity — the regional picture is what you actually need.

How a Small Trigger Becomes a Massive Blackout

The 2003 Northeast Blackout is the clearest illustration of why the “most frequent cause” conversation is distinct from the “most consequential failure” conversation. The trigger was mundane: overgrown trees contacted high-voltage transmission lines. By raw cause-coding, it would show up in the same category as thousands of routine tree-contact outages that year. But roughly 55 million people in the U.S. and Canada lost power, and restoration costs came in around $6 billion.

The tree didn’t cause all of that. The cascade did. The initial contact should have been manageable, but monitoring software failures and gaps in situational awareness allowed the fault to propagate — overloading adjacent lines, tripping more equipment, spreading across the interconnected grid faster than operators could respond. The tree was the spark. The scale came from a system that had no effective way to contain it once it started.

This is the failure mode that event-count statistics can’t capture. Routine outage data logs each event and moves on; it doesn’t measure how interconnected the grid is at the moment of failure, or how quickly an operator can respond, or whether the monitoring system will give them accurate information. A squirrel tripping a neighborhood transformer is a nuisance. A squirrel tripping a substation transformer at a moment of high grid stress, in a region with degraded monitoring, under specific load conditions — that’s a different event even if the initial cause is identical. The cascade is what you’re actually afraid of, and it’s invisible in the headline cause.

What “Less Than One Outage Per Year” Actually Means

Across the 2023 public-power dataset, the average customer experienced less than one sustained outage over the entire year. That number is technically accurate and operationally misleading in equal measure.

Averages in reliability data are flattened by geography. Customers in dense urban areas, with underground lines and shorter vegetation exposure, may go years without a sustained interruption. Customers in rural areas — longer lines, more trees, fewer redundant paths — can see several in a single season. The national average doesn’t belong to anyone in particular; it’s the midpoint of a very wide distribution.

The practical implication: if you’re thinking about outage preparedness, the national average is close to useless as a planning input. Your local history — how often your address or neighborhood has lost power, and for how long — is the number that actually matters. Utilities publish reliability statistics; your own memory is also data.

The Two Questions Worth Keeping Separate

Almost every apparent contradiction in outage data traces back to the same root: frequency and severity are different measurements, and sources pick whichever one serves their story. Vendors and utilities emphasize weather because weather dominates impact metrics — and because dramatic causes motivate preparedness spending. Operational datasets show trees and squirrels near the top because they count discrete events without weighting them by scale.

Neither answer is wrong. Both are incomplete on their own. If you want to know what’s most likely to cut your power on a random Tuesday, the answer is probably a tree limb or a failing transformer — not a hurricane. If you want to know what will leave you dark for the longest time or affect the most people when it happens, the answer is weather, and it isn’t close. Keep those two questions distinct, and the data stops contradicting itself.