Simulation

Last modified: 12 Feb 2025

The simulation in VCOM provides you with real-time solar power simulations for each of your PV systems. The simulation affects the following areas of VCOM:

• Solar power chart

• Variance analysis chart

• Loss breakdown chart

• Inverter simulation chart

• Control visualization chart

• Current system status portlet

• Smart alarms: see Simulation methods for smart alarms for configuration details

Configure the simulation

1. Navigate to Calculations > Simulation.

2. Select a percentage for the Target range.

3. Select the Simulation method.

We recommend selecting a simulation method and target range once and only changing it if you want to compare which options display the best results for your system. When making any changes, be sure to select Save. To view the updated solar power chart, navigate to Evaluation > Solar power chart > Refresh icon. If you change the simulation method, you do not need to perform a recalculation.

Target range

The Target range is a percentage (e.g. 10%) that is applied to the simulation's target value on the solar power chart. Data outside of this range is considered a yield loss. For information on calculating yield losses, see Yield loss calculation.

Simulation methods

The following methods are used to estimate theoretical production. The method you choose depends on your system setup and preferences.

Target PR

Default setting. It is a basic simulation where you can set your expected performance ratio overall or monthly as a percentage.

Prerequisites

• A G_M0 term must be defined. See Terms.

• You have manually configured the range at the system level under Calculations > Target PR.

Formula

Energy (simulated) [kWh] = Nominal Power[kW] x Irradiance [kWh/m²] x Target PR

Example

Energy (simulated) [kWh] = Nominal Power[kW] x Irradiance [kWh/m²] x Target PR
17111.43 = 10910.9 x 1.96036 x 80%

Physical simulation

The physical simulation uses additional parameters to provide more accurate results:

• Sensor irradiance: All irradiance sensors defined in a system are taken into account depending on how they fit the production. This includes sensors connected to the data logger and sensors defined as a term.

• Number of modules

• Module power: maximum power points in the VCOM subsystem setup

• Number of inverters

• Inverter output power: rated output power.

• Power control correction value

Prerequisites

• All inverters are assigned to a subsystem

• At least one working irradiance sensor

Info

Satellite data is used as a fallback if no sensor data is available and the system has a valid configuration. See Set up a new system.

The satellite data is based on the following site parameters: longitude and latitude, height above sea level, ambient temperature from weather models, module inclination and orientation, and whether a tracker is used.

Machine learning simulation (artificial intelligence optimized simulation)

Machine learning algorithms analyze the historically measured data of the PV system and optimize the physical simulation. The machine learning simulation allows you to learn site-specific characteristics such as shading, clipping, and degradation.

Prerequisites

• All inverters are assigned to a subsystem

• At least one working irradiance sensor

• 70% or more of the daytime data points are valid

• At least two weeks’ worth of valid training data within the last 30 days is available

Comparison of the physical simulation and machine learning simulation

The graphics below show how the physical simulation can be improved with machine learning, using clipping and shading as examples.

Example: clipping

Example: shading

Recalculate simulation

If you change a term, for example, an irradiance term, you may need to recalculate the simulation for the solar power chart.

Example: If a sensor malfunctions, you switch to another sensor. This requires you to recalculate the simulation to ensure accuracy.

Note

Switching from one simulation method to another does not require recalculation.