How Would Different Solar PV Systems Perform Under Tropical Environments?

Abstract In this paper, we analyze and compare the performance of six different solar PV technologies in tropical environments, using three years of performance data from a 1.2 MW experimental solar facility. The technologies considered include single-crystalline silicon, polycrystalline silicon, microcrystalline silicon, amorphous silicon, copper indium selenium (CIS), and hetero-junction with intrinsic thin layer (HIT). The field performances of these cells were initially assessed using standard performance indices such as Array Yield, Reference Yield, Capture Loss, Performance Ratio, and Efficiency Ratio. Among the technologies studied, amorphous silicon and HIT-based systems demonstrated superior performance, showing higher Performance and Efficiency Ratios, along with lower capture losses. This study also modelled the fluctuations in power production from these panels. Under probabilistic modeling, the ramping behavior of the systems was characterized using the Generalized Logistic Distribution. The HIT-based system showed the highest probability for fluctuations, while the ramp rates of the Micro-Crystalline Silicon and CIS-based systems were the lowest. To predict minute-wise and hourly ramping of the PV systems under varying levels of solar insolation, machine learning methods such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and k-Nearest Neighbors (kNN) were employed. With a Normalized Root Mean Square Error (NRMSE) of over 96%, these models demonstrated high accuracy in capturing the ramping characteristics of the studied PV systems. The results of this study offer valuable insights into the performance of different PV systems in tropical regions, which can be used in efficiently designing and managing solar PV projects.