Monitoring photovoltaic soiling: assessment, challenges, and perspectives of current and potential strategies

Bessa, João Gabriel; Micheli, Leonardo; Almonacid, Florencia; Fernández, Eduardo F.

doi:10.1016/j.isci.2021.102165

Cited by 64 publications

(29 citation statements)

References 151 publications

(376 reference statements)

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“…Similar studies indicate that for some locations, losses exceeding a 50% reduction in power output can be observed when left untreated for a year [6]. The deposition of dust has also been shown to cause permanent degradation of the surface properties of panels and limit the total service lifetime [7] because of uneven temperature distributions arising from non-uniform soiling [8].…”

Section: Introductionmentioning

confidence: 75%

Mathematical Modelling of a System for Solar PV Efficiency Improvement Using Compressed Air for Panel Cleaning and Cooling

King

Dooner

et al. 2021

Energies

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The efficiency of solar photovoltaic (PV) panels is greatly reduced by panel soiling and high temperatures. A mechanism for eliminating both of these sources of inefficiencies is presented by integrating solar PV generation with a compressed air system. High-pressure air can be stored and used to blow over the surface of PV panels, removing present dust and cooling the panels, increasing output power. A full-system mathematical model of the proposed system is presented, comprised of compressed air generation and storage, panel temperature, panel cleaning, and PV power generation. Simulation results indicate the benefit of employing compressed air for cleaning and cooling solar PV panels. For a fixed volume of compressed air, it is advantageous to blow air over the panels early in the day if the panel is soiled or when solar radiation is most abundant with the highest achievable flow rate if the panel is clean. These strategies have been shown to achieve the greatest energy captures for a single PV panel. When comparing the energy for air compression to the energy gain from cleaning a single PV over a two-week period, an energy ROI of 23.8 is determined. The system has the potential to eliminate the requirement for additional manual cleaning of solar PV panels.

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Section: Introductionmentioning

confidence: 75%

Mathematical Modelling of a System for Solar PV Efficiency Improvement Using Compressed Air for Panel Cleaning and Cooling

King

Dooner

et al. 2021

Energies

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“…This range of cleaning thresholds are the main values of CT presented in the literature. [4] The modeling analysis was run for a larger range of cleaning thresholds, from 0 to 20 mm day −1 as well. Data with p-values greater than 0.05 were excluded in the analysis, as considered not statistically significant.…”

Section: Resultsmentioning

confidence: 99%

“…[53] The analysis includes also data from the rainfall database (SODAPRO), sourced by MERRA-2 and originated from an European project funded by the European commission in 1999. [54,55] The main CT values presented in the literature are from 0 up to 10 mm day −1 [4] with fully and partial cleanings reported. To expand the analysis, a considerable number of thresholds (from 0 to 20 mm day −1 ) were tested in order to find the relationship between the accuracy of the models and some thresholds values distinct from those already presented in the literature.…”

Section: Cleaning Thresholdmentioning

confidence: 99%

“…[4] In addition, preventive actions can be part of the soiling mitigation strategy including system's configuration (e.g., tracking systems, site adaption, and site selection) and PV module characteristics (e.g., antisoiling coatings and optimized module design). [5][6][7][8] In order to achieve an optimal mitigation strategy, soiling monitoring is the key activity to be put in place, where a correct estimation of soiling is essential.There are several tools to estimate soiling, [4] with soiling stations being the most common solution. In order to reduce some disadvantages of these tools (i.e., human labor cost and maintenance, which can be expensive specially in remote locations), previous studies [9][10][11][12] have proposed estimation models, where soiling is estimated based on the variability and the interaction of environmental parameters, as well as on site characteristics and system configuration.The concept behind these estimation models is that the soiling profile of a PV system can be approximated to a sawtooth wave made of dust accumulation periods and cleanings.…”

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confidence: 99%

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Estimation of Photovoltaic Soiling Using Environmental Parameters: A Comparative Analysis of Existing Models

Bessa

Micheli

Montes‐Romero

et al. 2022

Advanced Sustainable Systems

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Soiling is the process where dust, dirt, and organic/inorganic contaminants accumulate on the surface of a photovoltaic (PV) module. It impacts the energy generation of PV systems and causes significant economic losses. It can be monitored through soiling estimation models, which evaluate its impact depending on a number of environmental parameters. The main focus of this study is to compare four existing estimation models in Jaén, Spain, and to analyze their performance in an environment different than that where each of them is developed. The results indicate that all models can reproduce accurately the seasonality of soiling in Jaén, if a cleaning threshold of 0.3 mm day−1 is considered. The models’ performance is found to be influenced not only by the mass concentration but also by the optical properties of each component of the atmospheric particulate matter, with an overestimation up to 4% in high organic carbon concentration periods. The natural cleaning role of rainfalls and its influence on the modeling error are also discussed through the paper.

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“…The dust accumulated on the surface of the photovoltaic panel comes mainly from the soil, rocks, construction debris, particles from car traffic, bird droppings, and pollen [13]. Dust accumulation on the surface of the panels obstructs the light, preventing it from reaching the PV cells, reducing energy production [14,15]. The energy loss depends on the amount of dust, particle size, and chemical composition of the powder.…”

Section: Introductionmentioning

confidence: 99%

The Use of Drone Photo Material to Classify the Purity of Photovoltaic Panels Based on Statistical Classifiers

Czarnecki

Bloch

2022

Sensors

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The subject of this work is the analysis of methods of detecting soiling of photovoltaic panels. Environmental and weather conditions affect the efficiency of renewable energy sources. Accumulation of soil, dust, and dirt on the surface of the solar panels reduces the power generated by the panels. This paper presents several variants of the algorithm that uses various statistical classifiers to classify photovoltaic panels in terms of soiling. The base material was high-resolution photos and videos of solar panels and sets dedicated to solar farms. The classifiers were tested and analyzed in their effectiveness in detecting soiling. Based on the study results, a group of optimal classifiers was defined, and the classifier selected that gives the best results for a given problem. The results obtained in this study proved experimentally that the proposed solution provides a high rate of correct detections. The proposed innovative method is cheap and straightforward to implement, and allows use in most photovoltaic installations.

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Monitoring photovoltaic soiling: assessment, challenges, and perspectives of current and potential strategies

Cited by 64 publications

References 151 publications

Mathematical Modelling of a System for Solar PV Efficiency Improvement Using Compressed Air for Panel Cleaning and Cooling

Mathematical Modelling of a System for Solar PV Efficiency Improvement Using Compressed Air for Panel Cleaning and Cooling

Estimation of Photovoltaic Soiling Using Environmental Parameters: A Comparative Analysis of Existing Models

The Use of Drone Photo Material to Classify the Purity of Photovoltaic Panels Based on Statistical Classifiers

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