Photovoltaic-thermoelectric (PV-TE) hybrid device is one of the most representative ways for the full spectrum solar energy utilization. The concentrator and nanostructured front surface have become important approaches to improve the conversion efficiency of the PV-TE device by enhancing the solar energy absorption. However, the concentrator causes badly non-uniform absorbed irradiance distribution of the PV-TE device surface, which has a great influence on the conversion efficiency of the PV-TE device. In addition, due to the multi-scale problem, it is hard to study the combined effects of the concentrator and nanostructured surface on the absorbed irradiance distribution of the PV-TE hybrid device surface. In this paper, a 3D model for a concentrated PV-TE hybrid system that employs the PV-TE hybrid device with moth-eye nanostructures and a linear Fresnel reflective solar concentrator is established. For the multi-scale problem, a Monte Carlo-Finite Difference Time Domain (MC-FDTD) coupled method is presented. At first, three parameters including duty ratio, height, and diameter are used to analyze the influences of the moth-eye nanostructure dimension on the reflectance. Then, taking the effects of the sun shape, the slope error, and the polarization of incident electromagnetic wave into considerations, the comparison and analysis on the absorbed irradiance distributions of PV-TE surface under four different conditions (with plane surface, with nanostructured front surface, with concentrator and plane surface, with concentrator and nanostructured front surface) were conducted by the MC-FDTD coupled method. Eventually, based on the precious investigation, a novel way of using different dimensional nanostructures is proposed to improve the uniformity of the absorbed irradiance distribution. As a result, this approach not only improve the uniformity of absorbed irradiance distribution very well, but also can let the mean absorbed irradiance be raised 1.6 times to reach 7644.14 W/m(2) compared to plane surface. (C) 2017 Elsevier Ltd. All rights reserved.