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Policymakers have become eager to move towards sustainability recently due to the growing costs of electricity and concerns about the environment. Environment friendly and economical energy sources, such as solar power, are being introduced at increasing rates. Photovoltaic (PV) panels are considered an important method of harnessing solar power. Although solar energy is one of the most efficient renewable and sustainable sources of energy, the accumulation of dust and debris on even one panel in a PV array reduces the efficiency of energy generation, thus highlighting the need to keep the surfaces of PV panels clean. Several methods can be used to clean PV panels, such as Heliotex technology, electrostatic cleaning, the use of self-cleaning glass, automatic cleaning and manual cleaning. The Preference Selection Index (PSI) multicriteria decision-making approach is used in this study to compare these cleaning methods. Data were collected via a survey of solar energy experts in Jordan to enable a comparison of these cleaning methods, and several attributes were considered. After the initial PSI analysis, a follow-up sensitivity analysis was conducted that involved removing the cost attributes. The results showed that the best method was manual cleaning. The results of the sensitivity analysis confirmed that manual cleaning is the method most often preferred by experts. [ABSTRACT FROM AUTHOR]

• The effect of the shape factor on the efficiency of the flexible photovoltaic modules. • The performance of different shapes of the flexible photovoltaic modules. • The standard flat photovoltaic modules is the most efficient shape of the flexible photovoltaic modules. This study investigates the performance of different shapes of the flexible photovoltaic modules. Three shapes of the flexible modules were compared under similar outdoor conditions: The standard flat, convex, and concave. The comparison was based on the solar radiation input, voltage output, current output, and back of the module's temperature. Results showed that based on the output power and the efficiency for the modules, the standard flat module was of the highest performance, followed by the convex module and then by the concave module. The average output efficiency of the standard flat module was 4.5–6.0% and 0.8–1.2% for the convex module, while it was 0.46–0.53% for the concave module. In addition, a simulated energy analysis was carried out between the standard flat module toward the south direction and the convex module toward the southeast direction. The simulation results showed that an area that holds 50 standard flat modules, could hold 72 convex modules. Moreover, the annual ejected electrical energy into a grid for the standard flat modules and convex modules were 8.61 MWH and 5.462 MWH, respectively. Furthermore, the performance of the standard flat and convex modules were 74.79% and 70.96%, respectively. [ABSTRACT FROM AUTHOR]

Policymakers have become eager to move towards sustainability recently due to the growing costs of electricity and concerns about the environment. Environment friendly and economical energy sources, such as solar power, are being introduced at increasing rates. Photovoltaic (PV) panels are considered an important method of harnessing solar power. Although solar energy is one of the most efficient renewable and sustainable sources of energy, the accumulation of dust and debris on even one panel in a PV array reduces the efficiency of energy generation, thus highlighting the need to keep the surfaces of PV panels clean. Several methods can be used to clean PV panels, such as Heliotex technology, electrostatic cleaning, the use of self-cleaning glass, automatic cleaning and manual cleaning. The Preference Selection Index (PSI) multicriteria decision-making approach is used in this study to compare these cleaning methods. Data were collected via a survey of solar energy experts in Jordan to enable a comparison of these cleaning methods, and several attributes were considered. After the initial PSI analysis, a follow-up sensitivity analysis was conducted that involved removing the cost attributes. The results showed that the best method was manual cleaning. The results of the sensitivity analysis confirmed that manual cleaning is the method most often preferred by experts. [ABSTRACT FROM AUTHOR]