Data Analysis Report | Gajner, Bikaner, Rajasthan
Data Period: December 2024 - November 2025 (12 months) | Data Source: Historical export from existing data logger
Monthly Generation in GWh | ★ Best Month: April 2025
| Month | Actual (GWh) | Expected (GWh) | Gap | PR (%) | Peak Irradiance |
|---|---|---|---|---|---|
| Dec-2024 | 1.79 | 0.41 | +338.1% | - | 706 W/m² |
| Jan-2025 | 1.92 | 1.39 | +38.2% | 110.5% | 912 W/m² |
| Feb-2025 | 1.72 | 1.48 | +16.3% | 93.0% | 864 W/m² |
| Mar-2025 | 2.60 | 2.43 | +7.4% | 85.9% | 1036 W/m² |
| Apr-2025 | 2.69 | 2.46 | +9.4% | 87.5% | 1090 W/m² |
| May-2025 | 2.59 | 2.59 | -0.1% | 79.9% | 1117 W/m² |
| Jun-2025 | 2.26 | 2.36 | -4.1% | 76.7% | 1148 W/m² |
| Jul-2025 | 2.06 | 1.39 | +48.6% | 118.9% | 1144 W/m² |
| Aug-2025 | 2.16 | 1.59 | +35.6% | 108.5% | 1368 W/m² |
| Sep-2025 | 2.30 | 2.18 | +5.5% | 84.4% | 1186 W/m² |
| Oct-2025 | 2.22 | 1.87 | +18.9% | 95.1% | 989 W/m² |
| Nov-2025 | 1.73 | 1.32 | +31.6% | 105.3% | 772 W/m² |
Analysis of INV-01 through INV-10 shows 27 active strings per inverter with consistent current readings averaging 6.3A during peak hours. Strings 20, 29-32 show zero current - likely by design (not all string inputs utilized).
Current data export provides 10-minute interval readings with string-level granularity. However, PR values show anomalies (>100%) indicating potential irradiance sensor calibration issues or calculation methodology differences.
The plant is generating 21.4% above expected - excellent performance. This indicates good site conditions and proper O&M. With FluxAI, you could identify the specific factors driving this outperformance and replicate across other sites.
Some months show PR >100% (Jul: 118.9%, Jan: 110.5%) which is technically impossible. This suggests irradiance sensor calibration issues. FluxAI's AI would auto-flag these and correlate with weather data.
As mentioned in your email, historical fault logs are not captured. This means inverter trips, communication failures, and grid events go unrecorded - critical diagnostic data lost forever.
Data available only via Excel/PDF downloads. No API means no automation, no real-time alerts, and no Zoho integration. Your team spends hours on manual reporting.
Clear seasonal dip in Jun-Jul (2.26 & 2.06 GWh) due to monsoon cloud cover. June also shows the lowest PR (76.7%). FluxAI can correlate with weather APIs to set realistic seasonal targets and avoid false underperformance alerts.
Each inverter has 27 of 32 string inputs active (Strings 20, 29-32 unused). This is likely by design, but without documentation, it's unclear if this is optimal or represents 15% untapped capacity.
Peak irradiance consistently occurs between 11:30 AM - 1:00 PM. August recorded highest at 1,368 W/m². FluxAI can optimize cleaning schedules around these peak hours to maximize generation.
Current logger captures data every 10 minutes - good granularity. However, sub-minute spikes and transients are missed. FluxAI Edge captures every second for better fault detection.
May and June showed near-expected or below-expected generation (-0.1% and -4.1%). Without predictive alerts, you only discover shortfalls after the month ends. FluxAI provides daily tracking against targets.
With 12 months of data, panel degradation analysis is possible but not being done. FluxAI can track year-over-year string-level degradation to predict cleaning needs and panel replacements.
Your Lords site is performing well, but you're flying blind without real-time visibility, fault logs, or predictive analytics. With FluxAI, you'd have complete control over your data - stored on your AWS, accessible via API, and enhanced with AI-powered insights.