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Utility-Scale PV Performance Analysis & Diagnostics

Analyze utility-scale PV performance, diagnose generation anomalies, and generate technical reports

4.3(6 reviews)
10+ downloads
Updated Oct 2026
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What You Can Do

You can upload SCADA data, inverter logs, weather station readings, and system specifications to receive structured performance analysis. Claude interprets multi-variable datasets to diagnose generation anomalies, quantify specific loss categories (soiling, clipping, downtime), calculate availability-adjusted yields, and benchmark facility metrics against industry standards. The skill produces technical root cause reports suitable for O&M teams, insurance claims, and contractual performance disputes.

Features

SCADA & inverter data interpretation

Parse real-time datasets from Fronius, SMA, ABB and other platforms to identify performance trends and anomalies

Anomaly detection & loss quantification

Isolate and calculate losses from soiling, inverter clipping, equipment downtime, and weather deviations

Performance benchmarking

Calculate facility-level metrics (capacity factor, PR, availability) and compare against industry standards and P50/P90 forecasts

Multi-variable correlation analysis

Correlate generation deviations to external factors (irradiance, temperature, inverter efficiency, grid constraints)

Technical root cause diagnosis

Trace underperformance to specific equipment, operational issues, or environmental factors with supporting data

IEC 61724 & NREL POA methodology

Apply accepted international standards for yield assessment and performance ratio calculations

Defensible technical reporting

Generate structured reports with data interpretation, loss breakdowns, and documented methodology for contractual or insurance use

Example Output

Example 1: Soiling-Driven Performance Loss

Input: 30-day SCADA data showing 8% generation shortfall vs. forecast; POA irradiance nominal; ambient temp baseline.

Output:

code
Performance Summary
• Actual Yield: 1,847 MWh | Expected P50: 2,010 MWh | Variance: -8.1%
• Capacity Factor: 18.4% | Industry Benchmark: 21.2% | Loss: -2.8pp

Root Cause Analysis
1. Soiling Loss: 6.2% (dominant driver)
   - 14-day dust accumulation + 2 rain events insufficient for cleaning
   - POA transmittance degradation from 97% → 91%
2. Inverter Clipping: 1.1% (secondary)
   - Peak DC/AC ratio constraint during high-irradiance days
3. Weather Variance: +0.4% (favorable)
   - Cooler ambient temps offset irradiance shortfall

Recommendation: Schedule panel cleaning within 7 days; monitor soiling rate post-rain.

Example 2: Equipment Failure Diagnosis

Input: 15-day production data with sudden 35% drop on Day 8; inverter status logs; thermal imaging available.

Output:

code
Anomaly Detection: String B (500 kW) outage detected Day 8 06:00–Day 9 14:00
• Missing generation: 2,100 kWh attributed to inverter shutdown
• Inverter logs confirm: Ground fault alarm → automatic lockout
• Estimated impact: 0.8pp reduction in monthly capacity factor

Cause: Moisture ingress in combiner box; recommend recertification and seal replacement.

What's Included

  • SKILL.md instruction file with performance analysis methodology:
  • SCADA Data Template: Structured CSV schema for uploading inverter, string, and weather data
  • Loss Quantification Checklist: Framework for isolating soiling, clipping, downtime, and weather losses
  • Technical Report Template: Markdown structure for professional root cause analysis documentation
  • IEC 61724 Reference Guide: Performance ratio and energy yield calculation methodology

Who It's For

  • Solar plant engineers managing 5MW+ utility-scale installations
  • O&M teams diagnosing performance shortfalls and equipment failures
  • EPC contractors supporting warranty claims and contractual performance reviews
  • Independent engineers conducting third-party performance assessments
  • Renewable energy portfolio managers benchmarking fleet-wide metrics

Best For

  • Analyzing SCADA and inverter datasets to identify underperformance drivers
  • Quantifying generation losses by category (soiling, clipping, downtime, weather)
  • Diagnosing sudden production drops or anomalies with root cause analysis
  • Benchmarking facility metrics against P50/P90 forecasts and industry standards
  • Generating technical reports for contractual disputes, insurance claims, or O&M escalations

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