Trusted by 100+ MWp of Solar & BESS Operations
Technical Whitepaper • 10 pages
365-Day Soiling Forecast System
Physics-ML hybrid forecasting with uncertainty quantification and optimal cleaning schedule optimization for maximum ROI.
The Problem:
Fixed cleaning schedules waste money through over-cleaning in wet seasons and under-cleaning in dry seasons. Operators need data-driven scheduling optimized for their specific plant economics.
What You'll Learn:
- 365-day forecast horizon with physics baseline + ML corrections
- Uncertainty quantification: ±2% (30d), ±5% (90d), ±8-12% (365d)
- Seasonal modulation: 1.5x dry season (May-Sept), 0.5x wet (Oct-Apr)
- Rain cleaning model: >10mm = up to 95% restoration
- Exhaustive search optimizer tests 1-5 cleaning scenarios per year
- Example: 2 optimized cleanings vs 12 baseline → €109K net benefit, 1013% ROI
Based on: Research from NREL, Sandia Labs, IEEE studies, and operational data from 100+ MWp of GCC solar & BESS assets.
Want Custom Analysis for Your Plant?
Our UAE-based team can provide a free 15-minute data quality audit and custom ROI calculation.
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