Solar Runtime Calculator
Every solar surveillance trailer on the market makes a runtime claim. Most of those claims hold up only under ideal conditions — and most deployments aren’t ideal.
This map shows the best-case scenario for solar. The model assumes ideal panel angle, full sun for the chosen season, and no weather interference — the deployment scenario every solar trailer is sold against. Pick a region. Pick a season. Adjust the configuration. The math you’ll see is what solar can produce under those favorable assumptions. Real sites, with real obstructions and real weather, will deliver less.
How to Use this Tool
📍 Pin your location
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How runtime is calculated
Each grid point uses Typical Meteorological Year (TMY) solar irradiance data from the European Commission's PVGIS dataset, scaled to your selected panel wattage. Deployment runtime — how long the trailer can run before the battery is depleted — is computed as:
runtime (days) = usable battery kWh ÷ (load kW × 24 − solar kWh/day)
Usable battery capacity is the rated nameplate kWh multiplied by a depth-of-discharge factor that depends on the chemistry. AGM batteries use 65% of rated capacity — taking AGM below roughly 50% state of charge significantly shortens cycle life, so 65% is a sustainable working figure. LiFePO₄ batteries use 90% of rated capacity, because this chemistry tolerates deeper cycling without measurable wear.
Runtimes are capped at 90 days. When average daily solar production meets or exceeds daily load, the battery never net-discharges over a typical year and the system effectively runs on sunlight alone — those cells show in the 60–90 day band at the top of the gradient.
Solar data: PVGIS / JRC European Commission · 264 grid points · 2° resolution · TMY
What you're looking at
The pattern that emerges
Run enough scenarios, and a clear shape appears.
Reduce the power load enough, and most locations can sustain a solar-only trailer through most of the year. A single low-power camera with minimal analytics and no deterrent lighting is a forgiving configuration.
Add a realistic surveillance stack — PTZ cameras, 24/7 recording, edge analytics, deterrent lighting, cellular communications, cold-weather heating — and the picture changes quickly. Runtime contracts. Battery deficits appear. Winter becomes a problem long before you reach the northern half of the country.
Shift the same configuration into January, or push it north, and the gap widens. Days shorten. Sun angles flatten. Cloud cover and snow reduce panel output. The trailer that ran indefinitely in July may not survive a week in February.
You can compensate to a point. More panels, larger battery banks, and a smaller load. But you can’t manufacture sunlight that isn’t there. No solar-only configuration closes the gap completely in every location and season. That isn’t a marketing problem. It’s a physics problem.
Three questions to test against the map
If your team is evaluating a solar-powered platform — or auditing one already in the field — the model is most useful when you run it against the questions that actually determine uptime.
1) How long do you need the trailer to stay in the field?
Solar runtime isn’t only about whether the cameras stay on — it’s about how long the trailer can do its job before someone has to go retrieve it. When solar can’t keep up, the consequence is rarely a dramatic outage. More often, it’s a truck roll back to the yard, a recharge cycle, and a redeployment — with a coverage gap in the middle. The map shows how long your configuration can realistically remain deployed before it becomes the next item on someone’s schedule.
2) What does production look like at your latitude in January?
Summer averages flatter every solar trailer. Winter is where decisions get made, and where outages quietly accumulate.
3) Has anyone revisited the power budget since the original trailer was configured?
Camera counts grow. Analytics get added. Lighting and communications expand. Few power budgets are revisited as deployments evolve, and the gap between the original spec and the current load is where the trouble starts.
About the data
Solar irradiance values in this model come from PVGIS — the Photovoltaic Geographical Information System maintained by the Joint Research Centre of the European Commission. PVGIS is the standard reference used by solar engineers, researchers, and installers worldwide. It draws on roughly two decades of satellite observations to estimate how much sunlight reaches the ground at any given location and time of year. For sites in North America, PVGIS pulls its underlying data from the U.S. Department of Energy’s National Renewable Energy Laboratory.