Precision cleaning, engineered for utility-scale solar.
Integrated Solar Systems delivers patented, condition-based cleaning for utility-scale solar farms. Our machine-learning platform decides what to clean, when to clean it, and how, recovering yield that fixed schedules leave on the panel.
Patented in the United States.
A U.S. patent covers our machine-learning control of nozzle output and boom carriage movement. To our knowledge, the only such filing in condition-based panel cleaning.
Condition-based, not calendar-based.
The model decides per zone, per panel, per fluid, per pass. The boom only acts where the data says it should. Uniform cleaning is replaced by intentional cleaning.
Verified on every cycle.
Onboard cameras re-scan each pass and confirm the clean before moving on. Every decision is logged, every outcome auditable, every cycle recorded.
A complete service for solar-farm operators.
From the first audit to a long-running operations contract, our team takes responsibility for the cleanliness and performance of your array. The data to prove it comes standard.
Efficiency & ROI audits
We model your soiling losses against weather, latitude, and panel tilt. You receive a cleaning plan with a projected yield delta in $/MW. There is no commitment for the first assessment.
Cleaning system deployment
Engineering, installation, and commissioning of our patented boom + nozzle system on existing arrays. Multi-fluid, condition-based, autonomously scanned.
Operations & managed service
Ongoing monitoring of every cleaning cycle. Monthly performance reports, predictive maintenance, and a model that improves on your specific climate.
Built on a patent, refined in the field.
Every deployment teaches the next. Our model is trained on cycles run across deserts, coasts, and snow lines, and informed by direct observation of how panels actually behave when the dust falls.
U.S. Patent Filed
Our control method for nozzle output and boom carriage movement is the subject of a U.S. patent under Attorney Docket 20859/160410.
Decisions per zone
The boom cleans only where the data indicates a real yield gain. Calendar cleaning is replaced by intentional, model-driven action.
Right fluid, right pressure
Channels for water, deionized rinse, and a cooling-pulse regime, each governed by the model and triggered by panel state.
Every cycle on record
Onboard cameras verify each pass. Operations receive a monthly performance file with every cleaning decision logged.
The innovation behind every cycle.
Our cleaning system is protected by a U.S. patent that covers the use of machine learning to control nozzle output and boom carriage movement in solar-panel cleaning. To our knowledge, it is the only such patent in the field of condition-based cleaning.
A machine-learning method for solar-panel cleaning.
Our protected method controls the cleaning system, panel by panel, using a predictive model rather than a fixed schedule.
- 01
Inputs the field actually gives you.
GPS, weather, image analysis, panel power output, cleaning regime, timers, manual input, and historical data.
- 02
A model that forecasts soiling losses.
The system predicts which zones lose the most yield next, and how much fluid and pressure will recover it.
- 03
Machine-learned activation of nozzles and boom.
Outputs are computed per zone, per pass: which nozzle fires, at what pressure, while the boom carriage moves at the chosen speed.
Three steps from soiling to spotless.
Every cleaning cycle our system runs is a tight loop: sense the soiling, decide the right response, act on the panel, then verify it worked. The model learns from every pass.
Sense.
Onboard cameras and live panel-output data continuously map soiling and surface temperature across every zone of your array.
Decide.
The predictive model forecasts soiling loss and ranks zones by ROI. Some are cleaned today. Others are queued for tomorrow. Many are skipped entirely.
Act & verify.
The boom drives the carriage, opens the right nozzle with the right fluid at the right pressure, then re-scans to confirm the clean.
Designed for high-soiling environments.
The system is built for the climates that lose operators the most yield: dust-laden air, infrequent rain, hard water, long daylight cycles. Every input the patent describes is sampled live in those conditions.
One controller, three regimes.
From the patent itself: the model selects between cooling water spray, light spray density, and heavy spray density. The choice is made per zone, per panel, per cycle, using machine-learned activations of nozzle output and boom carriage movement.
- CoolingPulsed spray when panel temperature crosses a predetermined threshold.
- LightLow-density spray for routine condition-based passes.
- HeavyHigh-density spray for accumulated, high-loss soiling.
Let's talk about your farm.
Send us your site coordinates and a recent month of production data. We will come back with a cleaning plan based on the regimes covered by our patent.