In this document
This article explains how system unavailability losses (technical events — internal/external — and weather-incurred snow events) and long-term degradation (first-year ~0.8% LID plus ~0.5%/year thereafter, tracked via PVOUT specific/total and performance ratio) are modeled to produce realistic 25-year PV energy yield predictions.
Usage in Solargis platform |
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This model is used in Solargis Evaluate, particularly when configuring and simulating the PV energy system. |
Overview
System unavailability losses and long-term degradation are crucial parameters that significantly impact the actual energy yield of photovoltaic (PV) power plants.
While unavailability losses represent temporary interruptions or limitations in power generation due to technical and weather-related events, long-term degradation captures the inevitable decline in module performance over time. Understanding and accurately modeling these factors is essential for realistic energy yield predictions, financial planning, and operational strategy development.
System unavailability losses
System unavailability losses quantify the electricity losses incurred due to the shutdown or power output limitation of a PV power plant or its components. These losses can be categorized into two main types: Technical events and weather-incurred events.
Technical events
Weather-incurred events (snow)
Internal reasons: These include maintenance and failures of components, leading to Internal unavailability losses. This type of loss is set as a percentage reduction of produced electrical power.
External reasons: These losses arise from shutdowns or power limitations caused by factors outside the control of the PV power plant, resulting in external unavailability losses. A power grid limit is set, leading to a reduction in injected electrical active power at the energy delivery point.
Both internal and external unavailability losses apply to selected time steps in the temporal resolution of the simulated time series within internal calculations.
A special case of system unavailability losses occurs due to snow events. Even a thin layer of snow can block nearly all irradiation, rendering DC generation insufficient for inverter operation. In such cases, the PV system is considered unavailable due to snow on the PV modules, as the non-production is not caused by a lack of radiation or technical unavailability events. This type of loss is applied as monthly losses.
Comparison with other software
The treatment of system unavailability losses due to technical events across various solar simulation software:
Software | Parameter name | Notes |
|---|---|---|
Solargis Prospect | Technical availability | Including technical operational issues caused by PV power plant outages and grid unavailability. |
Solargis Evaluate | Unavailability losses: Internal External | PV power production losses due to: Internal issues – operational, malfunctions, service works on the PV power plant External issues – distribution grid unavailability. |
PVsyst | System unavailability | Unavailability of the system due to system failures or maintenance stops. |
SAM (NREL) | AC availability and curtailment | Operating losses are imposed on the system by factors other than the solar resource and system’s design, such as forced, scheduled, and unplanned outages or other factors that reduce the system’s AC power output (page 84). |
SolarFarmer (DNV) | Grid availability | The Grid availability effect quantifies the amount of energy lost because the electrical grid to which the PV plant is connected is not available to accept power. |
System unavailability losses - How does Solargis compare
- Evaluate is the only simulator that separates internal (plant-side) from external (grid-side) unavailability — a distinction that matters in bankability studies, where the two are typically negotiated separately with the lender and offtaker.
- Evaluate's implementation follows IEC Technical Specification 61724-3 for energy evaluation of photovoltaic systems, a standards-based approach not referenced for the other simulators.
- PVsyst models unavailability from system failures or maintenance stops, without a documented internal/external split.
- SAM's AC availability and curtailment and SolarFarmer's grid availability both focus primarily on grid-side/curtailment events, giving less visibility into plant-side outages specifically.
Long-term degradation
Long-term degradation in photovoltaic (PV) systems represents an irreversible reduction in power output over time, primarily manifesting as a gradual decline in module performance.
A typical PV module experiences a 1-2% degradation in its first year due to light-induced degradation (LID), followed by a more stable annual degradation rate of 0.5-0.7% in subsequent years. The degradation process is influenced by multiple factors, including thermal stress, UV exposure, humidity, mechanical stress, and environmental conditions, which can lead to various failure modes such as corrosion, delamination, and cell cracking.
At Solargis, we model long-term degradation as a post-simulation calculation to show its impact over a 25-year system lifespan1. The degradation analysis provides three key performance metrics:
PVOUT specific shows the power output per kilowatt peak installed (kWh/kWp), allowing comparison of relative performance degradation regardless of system size.
PVOUT total measures the absolute power generation in gigawatt-hours (GWh), reflecting the actual energy production decline over time.
Performance ratio (PR) indicates system efficiency by comparing the actual output to the theoretical maximum, helping track efficiency losses due to degradation.
Degradation modeling
We use a two-step approach for modeling degradation:
First-year degradation rate of 0.8% to account for initial performance drop.
Subsequent years at 0.5% annual degradation rate for the remaining system lifetime.
This modeling approach provides a realistic view of how PV system performance declines over its operational lifespan, enabling more accurate long-term energy yield predictions and financial planning.
Comparison with other software
The treatment of long-term degradation is comparable across various solar simulation software:
Software | Parameter name | Notes |
|---|---|---|
Solargis Prospect | Long-term degradation | Similar approach as in Solargis Evaluate |
Solargis Evaluate | Long-term degradation | User-defined options for first-year and annual degradation losses |
PVsyst | Degradation factor | User-defined settings for module degradation |
SAM (NREL) | Degradation | Includes provisions for long-term performance decline |
SolarFarmer (DNV) | Degradation | Accounts for long-term performance impacts |
Long-term degradation - How does Solargis compare
- Evaluate models degradation as a post-simulation calculation over a 25-year system lifespan, applying a distinct first-year rate before switching to a stable annual rate.
- Prospect uses the same approach as Evaluate, giving consistent long-term degradation treatment across both Solargis tools.
- PVsyst, SAM, and SolarFarmer all support user-defined degradation factors as well, so the core mechanism (first-year plus annual rate) is broadly comparable across all five simulators.
- The real differentiator is reporting: Evaluate surfaces degradation impact across three distinct metrics (PVOUT specific, PVOUT total, and performance ratio), giving a clearer view of where the decline shows up.