Module soiling by dust, snow, or other foreign materials will reflect and scatter some incoming irradiance and render it unavailable for photovoltaic conversion. The simplest approach is to model this as monthly irradiance loss coefficients that affect all irradiance components (diffuse & direct) with equal weight. The soiling level is defined by a vector of loss percentages, one for each month, as defined in the prediction’s Environmental Conditions.

 

Figure 31. Example Soiling Loss by Month

 

 

These loss factors are then translated into a soiling loss factor, or “soiling ratio”, μ_dirt,t which is a fraction close to unity, and is the complement of the soiling loss percentage.

For example, a loss coefficient of 0.99 corresponds to a 1% loss of irradiance due to soiling on the modules.

 

Inputs

 

Outputs

 

Algorithm

The soiling factor can be derived by three methods. All inputs indexed by i are defined as monthly values in the Environmental Conditions. The following algorithm assumes a loop through all timesteps, indexed by t.

Switching the Soiling Model Selection

1.) Case Off — Degenerate case: soiling factor is set to unity for all prediction timesteps regardless of the contents of the site (soiling loss percentage, etc.)

2.) Case On — Base case: soiling factor for the current prediction timestep is based on a lookup of the current monthly soiling loss, as defined in the monthly parameters of the Prediction Environmental Conditions.