Key Challenges in PV Cleaning Management

Fixed cleaning schedules lack flexibility, leading to high costs and low operational efficiency.

  • Limited Data Support

    No reliable data on soiling and power losses.

  • Lack of Scientific Guidance

    Cleaning decisions rely heavily on experience.

  • Hidden Energy Losses

    Soiling-related losses are often underestimated.

Data-Driven Intelligent Cleaning Strategy

euDustAnalyzer precisely compares the performance of soiled modules with clean reference modules to quantify power losses caused by soiling, enabling data-driven analysis and accurate determination of optimal cleaning timing.

Reference Module Options

Flexible configurations include on-site full-size modules and optional self-cleaning modules.

  • On-Site Full-Size Module

    High-accuracy option for research and testing. Requires regular manual cleaning.

  • Self-Cleaning Reference Module

    Automatic, water-free cleaning for O&M applications. No manual maintenance required.

Easy Deployment, Higher Returns

  • Increased Energy Output
    Optimize cleaning timing based on data insights to improve system performance and asset efficiency.
  • Unattended Operation
    Water-free auto-cleaning enables fully unattended operation, cutting maintenance costs.
  • Easy Installation
    Plug-and-play design with complete accessories and software for fast deployment.
  • Integrated Software Platform
    Visualizes soiling trends and features one-click calibration for simplified operation.