A Critical Appraisal of PV-Systems’ Performance

Climate change and global warming have triggered a global increase in the use of renewable energy for various purposes. In recent years, the photovoltaic (PV)-system has become one of the most popular renewable energy technologies that captures solar energy for different applications. Despite its popularity, its adoption is still facing enormous challenges, especially in developing countries. Experience from research and practice has revealed that installed PV-systems significantly underperform. This has been one of the major barriers to PV-system adoption, yet it has received very little attention. The poor performance of installed PV-systems means they do not generate the required electric energy output they have been designed to produce. Performance assessment parameters such as performance yields and performance ratio (PR) help to provide mathematical accounts of the expected energy output of PV-systems. Many reasons have been advanced for the disparity in the performance of PV-systems. This study aims to analyze the factors that affect the performance of installed PV-systems, such as geographical location, solar irradiance, dust, and shading. Other factors such as multiplicity of PV-system components in the market and the complexity of the permutations of these components, their types, efficiencies, and their different performance indicators are poorly understood, thus making it difficult to optimize the efficiency of the system as a whole. Furthermore, mathematical computations are presented to prove that the different design methods often used for the design of PV-systems lead to results with significant differences due to different assumptions often made early on. The methods for the design of PV-systems are critically appraised. There is a paucity of literature about the different methods of designing PV-systems, their disparities, and the outcomes of each method. The rationale behind this review is to analyze the variations in designs and offer far-reaching recommendations for future studies so that researchers can come up with more standardized design approaches.

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