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Micro-concentrator photovoltaics (micro-CPV) is a cutting-edge CPV approach aimed at increasing the efficiency and reducing the cost and carbon footprint of solar electricity by downscaling concentrator solar cells and optics. The reduced size of micro-CPV provides several advantages over conventional CPV, including shorter optical paths and lower temperature and resistive losses in the cell, resulting in higher electrical efficiencies. This may increase the energy yield per area compared to conventional CPV or silicon modules. Cost reduction is achieved through material savings and the use of continuous manufacturing methods enabled by the tiny size of cells and optics, such as roll-to-roll (R2R) and roll-to-plate (R2P) ultraviolet (UV) imprinting for optics production. However, adapting these processes to large-area arrays of Fresnel microlenses with no wasted areas and high efficiency remains a challenge. In this study, we present a comprehensive methodology for the development of micro-CPV optics with full area coverage–from design and mastering to up-scaling, tooling, and replication. The methodology involves designing a non-rotationally symmetric elementary insert tailored to ultraviolet imprinting. Crucially, multiple inserts are originated via precision machining and recombined to form a single array master mold without wasted areas. The master is then replicated into a flexible working stamp for UV imprinting of Fresnel lens arrays, utilizing different UV curable materials. The functional characterization of the lenses demonstrates an optical efficiency of 80% at 178X under collimated white light, representing the highest effective concentration achieved using UV-imprinted Fresnel lenses. Furthermore, initial reliability tests confirm the absence of degradation during thermal cycling or outdoor exposure. This methodology paves the way for continuous high-throughput manufacturing of microlens arrays using R2R or R2P methods, presenting a significant step for

A method for misalignments characterization through image acquisition has been adapted and applied to micro-CPV. For this purpose, a measurement set-up and an image processing are proposed and explained. Two different image processing are explored: one based on conventional segmentation method, and another based on Deep Learning. The method is validated based on two measurements that determine the accuracy and the repeatability, showing that the processing based on Deep Learning improves both measurement parameters.

The hybrid modules developed by a Swiss startup, Insolight, consist of a micro-concentrator photovoltaic (micro- CPV) sub-module mounted on a non-concentrator Si backplane. Embedding the micro-CPV cells on top of the flat plate module complements the high efficiency of the CPV with the geographic versatility of the Si cells. Characterization of such modules should be adapted for the requirements and challenges posed by the component submodules. The top CPV layer utilizes the direct component of the incident radiation and the bottom Si layer utilizes the diffuse component. Therefore, it is necessary to test the modules under two lighting conditions. This paper demonstrates a novel solar simulator design for the indoor characterization of hybrid modules based on the collimated-light solar simulator for CPV modules developed by the Instituto de Energía Solar-UPM. The new simulator design adds provisions for testing Silicon submodules under uniform diffuse light by incorporating diffusive elements in the collimated-light path and reducing stray light. The existing CPV simulator at UPM has been refurbished to test the new design concepts. The I-V curve of a hybrid module has been characterized indoors using several configurations and compared to reference measurements obtained outdoors in order to optimize and validate the new setup.

Micro-scale concentrator photovoltaics (micro-CPV) is an emerging trend for the development of high-efficiency, low-cost photovoltaic systems. The miniaturization of optics and cells offers advantages in terms of performance and enables differentiation in the PV market. However, the sub-millimeter size of the solar cells used, the intrinsic narrow angular tolerance of CPV optical systems (typically around 0.5° and 2°), and the massive number of cells per module lead to very tight mechanical tolerances. Therefore, determining the misalignments between cells and optics is important for quality control inspection of modules. In this paper, we describe a method for characterizing these misalignments based on image acquisition and its subsequent processing and apply it to a micro-CPV module composed of 572 lens-cell units. This method is validated, using a unique experimental technique that takes advantage of the tracking system embedded in the module. The statistical distributions of misalignments are compared for two tracking positions, residuals are determined and shows the consistency of the method. Finally, the impact of misalignment distributions on the IV curve of the module is discussed.