The enterprise friction point
NextEra operated 420 MW of utility-scale solar on rigid 60-day calendar washing schedules, losing 4–7% in uncaptured solar generation to dust and agricultural soiling. Premature washing during low-soiling periods wasted hundreds of thousands in water and cleaning labor.
Transformation objectives
- Connect plant SCADA historians (Modbus/OPC) and on-site pyranometer irradiance feeds.
- Isolate panel soiling losses from inverter electrical degradation using string I-V curve comparisons.
- Trigger economic panel washing dispatch when revenue loss exceeds the cost of cleaning.
Discovery & architectural audit
Telemetry audit showed that soiling accumulation varied by over 300% across different tracker blocks on the same solar farm due to local agricultural dust patterns, rendering uniform calendar cleaning highly inefficient.
The Fortiv AI architecture
- 01
Trimark & Nor-Cal SCADA Historian Ingestion Connectors: Streams 1-minute inverter string current/voltage telemetry and pyranometer irradiance.
- 02
Physics-Informed String Degradation & Soiling Models: Compares normalized performance ratios across neighboring tracker blocks to isolate soiling from hardware faults.
- 03
Economic Wash-Trigger & Local Weather Forecast Engine: Factors in real-time power revenue loss, cleaning labor costs, and 7-day rainfall forecasts.
- 04
Solar O&M Automated Work Order Dispatch Console: Generates prioritized panel washing tickets and string fault alerts for field technicians.
Verified audit outcomes
Post-deployment impact
- +3.6% Generation Lift
- Fleet energy output recovered across 420 MW of utility-scale solar operating capacity
- $840,000 Recovered
- In additional annual wholesale electricity revenue unlocked
- -32% Water Saved
- Water consumption reduced by eliminating premature and redundant panel washings
- 100% Software Driven
- Zero new sensors, drone cameras, or hardware instrumentation deployed
Architectural lessons learned
Comparing normalized string performance ratios across adjacent blocks isolates soiling from component faults with 99% accuracy.
Integrating local rainfall forecasts prevents dispatching wash crews right before natural rain cleaning events.
Future scale roadmap
Extending string telemetry diagnostics to automate single-axis tracker backtracking angles on overcast days.
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