In This White Paper, We Explore:

The Future of Machine Learning In Solar

• Dramatic improvements in symptom detection, root-cause diagnostics and optimized asset remediation are driving greater efficiencies through remote issue diagnosis and intelligent service responses.

Integrated Performance Assessment and Workflow Management

• Technical advances are enabling real-time forecasts of expected energy generation driven by live satellite imagery.
• Significantly improved workflows through remote diagnosis and targeting of high-priority alerts compared with low actionability noise (snow, temporary soiling).
• Advanced triage tools providing automated diagnosis along with production, service history and past performance, enabling rapid human intervention and service confirmation.

Breakthrough Analytics

• Unique access to data from hundreds of thousands of solar assets across the U.S. is driving unprecedented performance analytics by manufacturer, geography and local environments.
• Real-time performance analysis goes beyond field measurements which are often performed at the time of installation or activation therefore failing to assess changing conditions.
• Crisis management; the wildfires of 2020 drove analysis by region, tailoring real-time advice to homeowners in the context of fire zones and more urgent homeowner priorities.

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