###### Abstract  
Fossil fuels and their use to generate energy have multiple disadvantages, with renewable energies being presented as an alternative to this situation. Among them is photovoltaic solar energy, which requires solar installations that are capable of producing energy in an optimal way. These installations will have specific characteristics according to their location and meteorological variables of the place, one of these factors being soiling. Soiling generates energy losses, diminishing the plant's performance, making it difficult to estimate the losses due to deposited soiling and to measure the amount of soiling if it is not done using very economically expensive devices, such as high-performance particle counters. In this work, these losses have been estimated with artificial intelligence techniques, using meteorological variables, commonly measured in a plant of these characteristics. The study consists of two tests, depending on whether or not the short circuit current (Isc) has been included, obtaining a maximum normalized root mean square error (nRMSE) lower than 7%, a correlation coefficient (R) higher than 0.9, as well as a practically zero normalized mean bias error (nMBE). s +
Footnote †: journal: Applied Sciences  
1  
[PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]. Estimation of Soiling Losses from an Experimental Photovoltaic Plant Using Artificial Intelligence Techniques. _Appl. Sci._**2021**, _11_, 1516. [[https://doi.org/10.3390/app10141516](https://doi.org/10.3390/app10141516)]([https://doi.org/10.3390/app10141516](https://doi.org/10.3390/app10141516))  
11 November 2020  
Accepted: 1 February 2021  
the appropriate configurations, depending on the location and/or weather conditions. In this regard, it is worth mentioning the direct relationship between the atmospheric variables and plant optimization--irradiance, ambient temperature, relative humidity, and pressure, etc., are variables that must be taken into account when determining the best locations (within the same region of interest). Studies on this subject have shown that such variables are related to the place and circumstances where the plant is located [9; 10], as well as the possible presence (or not) of soiling, common in desert and other areas that may be in the path of intense soiling currents [11; 12]. In general, dust is the most studied pollutant to analyze the performance of solar photovoltaic systems. Dust soiling is a factor that has appeared and has been studied as photovoltaic solar systems have been built. Specifically, this phenomenon appears by covering the photovoltaic panels with a layer of dirt (causing deposition on the panels [13]), reducing the performance, and, consequently, the electrical production of each photovoltaic panel [14; 15]. Therefore, soiling becomes a fundamental issue in terms of optimization [16] and, thus, on photovoltaic plant production. The accumulation of soiling and dirt makes it more difficult for radiation to reach the panels, thus reducing performance [17; 18]. Desert climates are areas of the planet where these phenomena occur most, with particles being able to travel far from their place of origin [19]. As for the cycles of these currents, one could say that in the east of the European continent, they occur at the end of winters and in the west from June to September [20; 21]. However, there are other phenomena that can affect the production of a solar photovoltaic system. The location of the system is fundamental since it can be in the vicinity of an industry with waste in the atmosphere that can deposit on the panels, as is the case of mining in Chile [22], where the contaminants emitted into the atmosphere are usually deposited on the roof of the photovoltaic panels of the adjacent solar plants. Pollen is usually another phenomenon that is transported in the environment and, in rural areas, can end up precipitating on the field of photovoltaic panels whenever they are in nearby areas.