Uncertainty in energy estimations poses a significant challenge for engineers, financiers, and industry stakeholders. The Probability estimation feature helps you overcome this challenge, by identifying and accounting for the most crucial sources of uncertainty:
- Weather variability (GHI interannual variability)
- Modeling uncertainties (PV module, PV module quality, inverter, soiling)
You can access it under the Project parameters menu on the left.
Weather variability
Variability in the weather conditions directly affects the Global Horizontal Irradiance (GHI) and, consequently, the amount of energy the solar panels can produce.
The interannual variability refers to the variations in GHI from year to year, and is crucial for accurately predicting solar energy production over multiple years.
To add a GHI interannual variability:
1. Activate the toggle
2. Insert the value in the field available (0-25)
The field cannot be empty, and must include a value between 0 and 25.
By default, PVcase Yield provides a suggested value for GHI interannual variability. This value is determined by:
- The location you selected on the Meteo page
- The comprehensive research of Ineichen (2011)
This ensures that you have a reliable starting point based on established scientific findings.
Modeling uncertainties
Modeling uncertainties arise from the inherent imperfections and assumptions in the models used to predict energy yield. In PVcase Yield, you can account for different types of modeling uncertainties:
- PV module
- PV module quality
- Inverter
- Soiling
To add modeling uncertainties:
1. Activate the toggle.
2. Insert a value in the field available (0-25)
Combined uncertainty
Based on the percentages you inserted in the corresponding fields, PVcase Yield will calculate the Combined uncertainty value and display it at the top of the section:
The Combined uncertainty is then used in the calculation of probability values (P50, P75, P90, P95, and P99). You can access these values both on the Results page and within the generated PDF reports. This way, you will have a transparent view of potential energy estimates under different probability scenarios.