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Leverage this game-changing loss-estimation feature in LocusNOC™ to reach new levels of efficiency & cost-reduction

Understand how to detect discrepancies that arise between measured & modeled system performance

Locus Energy’s Virtual Irradiance (VI) Performance Waterfall is a tool that analyzes the power generation data from a meter to determine whether the panel(s) and inverter(s) behind the meter are working as expected. For systems that are not performing to expectations, the VI Performance Waterfall helps determine why discrepancies arise between measured and modeled performance of a system.

The VI Performance Waterfall first calibrates a PV model, based on measured energy data from the site, to create an accurate as-built estimation. Leveraging VI as the source of irradiance data, the Performance Waterfall then analyzes the differences between the modeled and measured data series to estimate underperformance due to clipping, snow cover, partial system downtime, soiling, shading, and degradation.

“Since the model is based on Locus Energy's VI engine, the Performance Waterfall avoids data collection issues such as sensor shading, soiling, calibration issues, or installation errors. The inferred modeling calibration also eliminates the need for meta-data and creates a true as-built estimation.”

Locus Energy Virtual Irradiance Performance Waterfall

PRODUCT OVERVIEW

Delivery: Cloud-based, online dashboard

Frequency: Real-time data delivery

Location: Global

Subscribe: sales@locusenergy.com or 877-562-8736

Portfolio Application

Learn About Solar Generation Growth & Future Impacts in ERCOT

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Locus' Virtual Irradiance Performance Waterfall provides:

  • Energy loss estimates for
    • Soiling
    • Clipping
    • Shading
    • Snow
    • Downtime
    • Partial capacity
    • Degradation
  • Loss estimates available as modeled data fields in the Locus Charting Tool, Reporting Interface, Excel Datalink, or external API

Portfolio Application

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Virutal Irradiance Performance Waterfall users:

  • Get a better understanding of the as-built performance of your solar assets
  • Reduce costs by avoiding unnecessary truck rolls for issues that do not need to be remediated, such as some shading and snow loss issues
  • Increase fleet productivity by identifying the type of partial capacity losses, extreme degradation, or extreme soiling cases that may have otherwise gone undiagnosed and untreated
  • Improve feedback loops and quoting processes by comparing design assumptions for losses with real-world performance data

Portfolio Application