Two-Step Nested Optical-Electrical Monte-Carlo Approach to Analyze the Influence of Tolerances on Micro-CPV Module Performance

In manufacturing and product optimization, understanding the influence of tolerances, which are inevitable variations in production processes, is crucial for enhancing performance while managing costs. However, previous analytical approaches lacked the capability to quantitatively assess the cumulative effect of multiple tolerances due to their random combination and statistical independence. In this work, we introduce a novel method that overcomes these limitations by effectively modeling complex dependencies among tolerances through a two-step nested Monte-Carlo approach. We apply this model to a micro-CPV module developed at Fraunhofer ISE. First, we randomly select and combine tolerances in a cell-lens unit using ray tracing. Then, we randomly select and combine these units in a full 690-cell module using an electrical network model considering different angles of incidence. The considered tolerances include deviations in component geometries and displacements and are based on measurements. The model predicts the acceptance angle and allows to identify the optimal interconnection schemes. Further, it is capable to determine the maximum tolerances permissible for maintaining a certain module power. While tolerances lead to a distribution in current generation among the cell-lens units, we find that parallel interconnections can compensate for such variations. Further, we identify that the positions of secondary lens and micro solar cell are the most sensitive parameters for achieving high module power. These findings are crucial for refining module design cost-effectively. Moreover, the model facilitates a quantitative assessment of optimization potentials, guiding decision-making in product development and manufacturing, and a techno-economic optimization.