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PlantPredict calculates uncertainty estimates to express the range of possible energy production outcomes. The uncertainty analysis combines multiple independent error sources to produce exceedance probability values (P50, P75, P90, P99) that characterize the likelihood of achieving specific energy production levels.

Uncertainty Components

PlantPredict uses five independent uncertainty components that are combined using the root-sum-of-squares method. Each component represents a distinct source of prediction uncertainty.
ComponentSymbolUnitsDescription
Interannual Variabilityσint\sigma_{\text{int}}%Year-to-year variation in solar resource at the site location
Irradiance Measurement Accuracyσsens\sigma_{\text{sens}}%Uncertainty in the irradiance sensor measurements used to develop the weather dataset
Monitoring Period Representativenessσmon\sigma_{\text{mon}}%Uncertainty from the monitoring period not fully representing long-term conditions
Spatial Variabilityσspa\sigma_{\text{spa}}%Uncertainty from extrapolating point measurements to the entire site area
Modeling Accuracyσmodel\sigma_{\text{model}}%Uncertainty in the PV performance model algorithms

Total Uncertainty Calculation

Total Irradiance Uncertainty

The total irradiance uncertainty combines all irradiance-related error sources: σirr=σint2+σsens2+σmon2+σspa2\sigma_{\text{irr}} = \sqrt{\sigma_{\text{int}}^2 + \sigma_{\text{sens}}^2 + \sigma_{\text{mon}}^2 + \sigma_{\text{spa}}^2} This represents the combined uncertainty in the solar resource estimate, independent of the PV modeling uncertainty.

Total Energy Uncertainty

The total energy uncertainty combines the irradiance uncertainty with the modeling accuracy: σtotal=σirr2+σmodel2\sigma_{\text{total}} = \sqrt{\sigma_{\text{irr}}^2 + \sigma_{\text{model}}^2} This represents the overall uncertainty in the predicted energy production.

Exceedance Probability Calculation

PlantPredict uses a normal distribution assumption to calculate exceedance probabilities. The P50 value represents the median expected production (50% probability of exceedance), while higher P-values (P75, P90, P99) represent increasingly conservative estimates with higher probabilities of being achieved.

Z-Score Application

For each exceedance probability level, a z-score is applied to adjust the P50 result: For irradiance-based metrics (GHI, POA Insolation): ValuePx=ValueP50×(1zx×σirr)\text{Value}_{P_x} = \text{Value}_{P50} \times (1 - z_x \times \sigma_{\text{irr}}) For energy-based metrics (Plant Net Energy, Specific Yield, Capacity Factor): ValuePx=ValueP50×(1zx×σtotal)\text{Value}_{P_x} = \text{Value}_{P50} \times (1 - z_x \times \sigma_{\text{total}}) where zxz_x is the z-score corresponding to exceedance probability xx.

Standard Z-Score Values

The z-score represents the number of standard deviations from the mean in a normal distribution:
Exceedance ProbabilityZ-Score
P500.000
P750.674
P901.282
P951.645
P992.326

Metrics Adjusted by Uncertainty

The following summary result metrics are adjusted for each exceedance probability level: Irradiance-adjusted metrics (using σirr\sigma_{\text{irr}}):
  • GHI Sum
  • POA Insolation
Energy-adjusted metrics (using σtotal\sigma_{\text{total}}):
  • Plant Net Energy
  • Plant Gross Energy
  • Array Net Energy
  • Block Net Energy
  • Specific Yield DC
  • Specific Yield AC
  • AC Capacity Factor
  • Total BoS Loss
  • Nighttime Losses
  • ESS PV Energy
  • ESS Battery Energy
Derived metrics:
  • Performance Ratio is recalculated from the adjusted Specific Yield DC and POA Insolation values

Example Calculation

For a prediction with the following uncertainty inputs:
ComponentValue
Interannual Variability (σint\sigma_{\text{int}})3.0%
Irradiance Measurement Accuracy (σsens\sigma_{\text{sens}})5.0%
Monitoring Period Representativeness (σmon\sigma_{\text{mon}})2.0%
Spatial Variability (σspa\sigma_{\text{spa}})2.0%
Modeling Accuracy (σmodel\sigma_{\text{model}})2.9%
Step 1: Calculate total irradiance uncertainty σirr=3.02+5.02+2.02+2.02=9+25+4+4=42=6.48%\sigma_{\text{irr}} = \sqrt{3.0^2 + 5.0^2 + 2.0^2 + 2.0^2} = \sqrt{9 + 25 + 4 + 4} = \sqrt{42} = 6.48\% Step 2: Calculate total energy uncertainty σtotal=6.482+2.92=42+8.41=50.41=7.10%\sigma_{\text{total}} = \sqrt{6.48^2 + 2.9^2} = \sqrt{42 + 8.41} = \sqrt{50.41} = 7.10\% Step 3: Calculate P90 energy value For a P50 Plant Net Energy of 100 GWh: EnergyP90=100×(11.282×0.0710)=100×0.909=90.9 GWh\text{Energy}_{P90} = 100 \times (1 - 1.282 \times 0.0710) = 100 \times 0.909 = 90.9 \text{ GWh}

Interpretation

  • P50: The median expected value; there is a 50% probability that actual production will exceed this value
  • P75: A moderately conservative estimate; 75% probability of exceedance
  • P90: A conservative estimate commonly used for financing; 90% probability of exceedance
  • P99: A highly conservative estimate; 99% probability of exceedance
The uncertainty values are user-specified inputs that should reflect the specific characteristics of the project’s solar resource assessment and the confidence in the modeling methodology.