Contamination of power line insulators is determined by air pollutants and can alter their functionality, leading to voltage drops or grid service interruptions.

Over the years, RSE has carried out several studies aimed at defining a forecasting system capable of simulating the fouling phenomenon of insulators. In particular, a prediction chain based on the air quality model CAMx, the meteorological model WRF, the anthropogenic emissions model SMOKE and the natural emissions models MEGAN and SEASALT has been implemented since 2016. It is capable of estimating the ground deposition phenomenon and the concentrations of the main pollutants to which insulators are exposed in the atmosphere. Since the first implementation of the modeling system, several updates and improvements have been introduced with the aim of making the tool increasingly efficient and reliable.

In particular, in the present year of research, the air quality forecasting system was first consolidated through an update of its main modules (CAMx, WRFCAMx, ISPRA 2015 emission inventory) in order to bring them up to date.

Downstream of this, the updated forecasting system included a module for calculating deposition on the surface of the insulator through a parameterized analytical formulation that takes into account a standardized insulator geometry and the local fluid dynamic characteristics of the deposition process. From the returned deposition values, it is then possible to calculate indices of insulator contamination (e.g., ESDD and NSDD).

Finally, it was decided to explore the possibility of including, downstream of the obstacle model, a model that would allow consideration of the thermodynamic transformations and phase changes undergone by the deposited compounds, as a function of temperature and relative humidity conditions.

For this purpose, the thermodynamic model ISORROPIA, already present in CAMx for simulating the thermodynamic equilibrium of inorganic species in the atmosphere, was considered. The two versions analyzed, 2.1 and 1.7, differ in the presence or absence of the alkaline earth metals (Mg2+, Ca2+ and K+).
The results showed that the ISORROPIA 2.1 model reconstructs the expected trend for some salts, such as sodium chloride, sodium nitrate, and ammonium sulfate. In other cases, the response output of the model exhibits trends deviating from the expected ones, while maintaining recurring behaviors in the presence of some salts in input.

The development of both the obstacle model and the thermodynamic model represent a peculiar aspect of the modeling system, so that in the continuation of the activity, special emphasis will be given to verifying the current limitations and improving their performance.