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Abstract
Regions with limited space for constructing renewable power generation systems need to maximize electricity generation by optimizing the operational efficiency of existing plants and selecting an optimal location for the new construction of PV power plants with favorable weather conditions and surrounding environment. Utilizing monthly input and output data, including four inputs (solar irradiation, temperature, number of modules, and photovoltaic (PV) array rated capacity) and one output (electricity generation) from utility-scale PV power plants, meta-frontier data envelopment analysis was employed in this study to identify factors contributing to power generation inefficiency. Additionally, a Monte Carlo experiment analyzed the impact of solar irradiation uncertainty on power generation efficiency. The findings revealed that the average power generation inefficiency during the study period was 0.445, primarily attributable to seasonal and technical factors. Since these factors are difficult to control once a power plant is in operation, it is important to select an optimal site for power plants by considering meteorological and geographical data. Moreover, the results indicated a significant gap between observed and simulated values of power generation efficiency, arising from variations in weather conditions, power plant site area, and the data used in the research. Employing PV modules with higher electricity output levels can boost the DC/AC ratio, thereby increasing power generation, enhancing efficiency, and contributing to a stable power supply, thus reducing daily and seasonal fluctuations in power generation.