Dust accumulation on the photovoltaic (PV) surface decreases the solar radiation penetration to the PV cells and, eventually, the power production from the PV system. To prevent dust-based power losses, PV systems require frequent cleaning, the frequency of which depends on the geographical location, PV integration scheme, and scale of the PV power plant. This study aims to measure the drop-in radiation intensity, as well as power output, due to dust and to determine the optimal time interval for PV cleaning in the United Arab Emirates (UAE) climate. In this research, a dusting study experiment was carried out at the Renewable Energy Laboratory, Falaj Hazza Campus, UAE University, Al Ain, UAE, for 3.5 months, from 22 April 2018 to 7 August 2018. To measure the pure radiation losses caused by the dust, four transparent glasses were used to mimic the top glass cover of the PV modules. The dusting induced power losses were measured for four selected PV cleaning frequencies (10 days, 20 days, 1 month, and 3 months). This study revealed that up to 13% of power losses occurred in PV panels that remained dusty for 3 months, compared to panels that were cleaned daily. PV cleaning after 15 days brought the losses down to 4%, which was found the most feasible time for PV cleaning in this study, considering a reasonable balance between the cleaning cost and energy wasted due to soiling.
The worldwide electricity supply network has recently experienced a huge rate of solar photovoltaic penetration. Grid-connected photovoltaic (PV) systems range from smaller custom built-in arrays to larger utility power plants. When the size and share of PV systems in the energy mix increases, the operational complexity and reliability of grid stability also increase. The growing concern about PV plants compared to traditional power plants is the dispersed existence of PV plants with millions of generators (PV panels) spread over kilometers, which increases the possibility of faults occurring and associated risk. As a result, a robust fault diagnosis and mitigation framework remain a key component of PV plants. Various fault monitoring and diagnostic systems are currently being used, defined by calculation of electrical parameters, extracted electrical parameters, artificial intelligence, and thermography. This article explores existing PV fault diagnostic systems in a detailed way and addresses their possible merits and demerits.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.