After a thunderstorm, a relay trip is usually the easy part. The hard part is what comes next: Where did the strike land, what did it stress, and do you need a crew immediately—or just a daylight inspection? Without a clear answer, teams default to wide patrols, conservative switching decisions, and “replace it to be safe” repairs that are expensive in both time and outage risk.
This guide breaks down lightning detection and monitoring in practical terms for utility operations: what it can tell you, the main technology paths, and the checklist you can use to evaluate a solution for distribution or transmission corridors.
What “Lightning Detection & Monitoring” Means in Utility Operations
In a utility context, lightning detection and monitoring is not just “seeing lightning on a map.” It’s the ability to connect a lightning event to the assets you operate—a corridor, a structure range, or a specific span— fast enough to influence dispatch, patrol routing, and post-storm triage.
Most programs combine two layers: (1) a regional view of lightning activity (useful for situational awareness and storm staging), and (2) an asset-correlated layer that helps you decide what to inspect and in what order.
How Lightning Actually Creates Work Orders
Lightning doesn’t always “blow something up” on contact. More often, it creates a spectrum of stress: from a temporary flashover that clears on a successful reclose, all the way to mechanical or insulation damage that becomes a permanent fault. What matters is how that stress shows up in the field.
1) Flashover and insulation stress
A flashover across an insulator string can be temporary, but it can also leave behind tracking, puncture paths, or hardware damage that turns into a repeat outage later. Polymer housings, porcelain, and glass all fail differently, which is why “it reclosed” is not the same as “it’s fine.”
2) Backflashover risk driven by grounding and geometry
When a stroke terminates on shield wire or a structure, the tower potential can rise fast. If the grounding path is poor (high footing resistance, dry soil, damaged counterpoise, etc.), a backflashover becomes more likely. This is one reason lightning performance work often pairs monitoring with grounding improvement and insulation coordination.
3) Conductor and hardware damage on severe events
The strongest strokes can create localized heating and mechanical stress. Typical peak lightning currents are often discussed in the tens of kA, while extreme events can exceed 200 kA. That’s why a “strike happened” is not enough—utilities want some way to rank events by severity and likelihood of damage. (For background on lightning current ranges, see industry lightning protection references.)
Three Technology Approaches You’ll See
A) Satellite / regional lightning products
Satellite-based lightning mappers are excellent for storm evolution and regional lightning trends. They’re not designed to tell you which specific tower hardware to inspect. Their spatial resolution is typically measured in kilometers, which is fine for forecasting, but often too coarse for dispatch decisions on long corridors. For example, NOAA’s Geostationary Lightning Mapper (GLM) is a weather-operations instrument with near-uniform resolution on the order of ~10 km. NOAA GLM overview
B) Ground-based lightning location networks
Ground-based networks can provide much tighter strike locations than satellite products. They’re widely used for lightning awareness, storm reporting, and risk analytics. The limitation is operational: even “hundreds of meters” can still cover multiple structures or spans, especially in dense corridors or rugged terrain. That means they’re a strong input, but not always a complete answer for patrol routing.
C) Line-mounted sensing and asset-correlated monitoring
Asset-correlated solutions aim to tie an event to your infrastructure more directly—often by capturing fast transient signatures and correlating them with known line topology, time stamps, and sensor placement. In practice, this can reduce the “search space” for crews from “patrol miles of line” to “inspect this segment first, then this one,” which is exactly where time and cost tend to leak.
One practical design note: the value of any monitoring layer depends on uptime. If your node goes dark during storms or low-load windows, it will miss the events you care about most. That’s why many utilities evaluate power architecture early, including CT harvesting and hybrid designs. If you’re comparing power approaches, this overview is useful: self-powered sensors with CT energy harvesting.
Buyer Checklist: What to Evaluate in a Lightning Monitoring System
Here’s the checklist I use when reviewing lightning monitoring proposals. Notice that very little of it is about “cool analytics.” The core question is whether the system will reduce uncertainty fast enough to change field decisions.
- Location usefulness: Does the output narrow you to a specific corridor segment or structure range, or is it still “somewhere in this area”?
- Latency: Do you see the event quickly enough to influence dispatch and switching plans, not hours later in a report?
- Event context: Can you distinguish “storm nearby” vs “event likely on this circuit,” and do you get severity cues for triage?
- Workflow integration: Can it feed OMS/SCADA or your dispatch tools without manual copy/paste and screenshots?
- Communications resilience: How does it behave during backhaul outages—buffering, store-and-forward, redundancy?
- Power architecture: What keeps it online during low-load periods and post-event windows?
- Installation and maintenance: Live-line considerations, mount method, inspection burden, and how you update/verify configuration.
If you’re building a corridor node that has to stay online in remote spans, you’ll also want to think in layers: a “power layer” that is utility-grade, and a “payload layer” (sensing + comms) that can evolve over time. For reference, see LinkSolar’s Overhead Line Power Platform and the broader Overhead Line Power Supply for Monitoring architecture options.
Deployment Playbook: Start Small, Validate Fast, Then Scale
Lightning monitoring programs succeed when they’re treated like an operations workflow, not a one-time hardware purchase. A practical rollout usually looks like this:
- Risk screening: Identify the corridors where lightning drives repeat outages, heavy patrol hours, or costly equipment stress.
- Pilot design: Choose a segment that produces measurable outcomes (patrol hours, restoration time, repeat outages, inspection findings).
- Commissioning validation: Confirm that events correlate to real inspection findings and that the output is operationally usable.
- Dispatch rules: Define “what triggers a truck roll” vs “what triggers a scheduled inspection,” and document it.
- Scale plan: Expand to additional segments once the workflow is proven and the data is trusted.
ROI: The Levers That Usually Matter
Lightning monitoring ROI is rarely about preventing lightning (you can’t). It’s about reducing the cost of uncertainty. In most utilities, the biggest levers are:
Fewer blind patrol miles (drive directly to the most likely segment first), fewer repeat trips (show up with the right hardware), and better prioritization after a storm (inspect where the risk is highest, not where access is easiest).
A simple way to model value is: (patrol hours avoided × fully loaded crew cost) + (restoration time reduced × your outage cost model) + (avoidable secondary damage found earlier). Use your own storm history and crew rates—generic averages can mislead.
Common Misconceptions
“We already have lightning data—so we’re covered.”
Regional lightning products are useful, but they’re often not asset-native. If your dispatch decision needs tower/span-level confidence, you’ll likely need an additional layer that correlates events to your topology and inspection workflow.
“If it reclosed, there’s no risk.”
Successful reclosing can still leave stressed insulation, damaged fittings, or contamination paths that show up later. The question is whether you can target inspection to the right segments instead of patrolling the entire corridor.
“We can just open devices before the surge arrives.”
Lightning surges propagate extremely fast along conductors. Operations-grade value comes less from “beating the surge” and more from knowing where to inspect, what to prioritize, and how to reduce outage time once protection has operated. (For the engineering side of lightning performance improvements on overhead lines, IEEE offers a dedicated guide: IEEE Std 1410.)
Where Lightning Monitoring Fits in a Broader Reliability Program
Lightning monitoring is most effective when it’s treated as one module inside a reliability stack. Utilities often pair it with fault location, conductor temperature, clearance/sag risk, or condition monitoring—then use a single workflow to route crews based on the highest-risk indicators after a storm. If you’re building that broader approach, this guide is a good starting point: predictive maintenance planning with power line monitoring.
Next Step
If you want to evaluate lightning monitoring for a specific corridor, the fastest path is to map your storm history to real field outcomes: which segments generate repeat truck rolls, which events become permanent faults, and where inspection findings cluster. Share that context and you’ll get a much cleaner system design than starting from sensor spacing alone.
If you’d like, send your corridor basics (voltage class, approximate miles, comms constraints, and typical load profile) and we’ll outline a practical pilot architecture and validation plan. Contact LinkSolar here.
