Performance enhancing solar energy absorber with structure optimization and absorption prediction with KNN regressor model

Abstract

We used the honeycomb resonator structure and explored its absorptance response in the visible, ultraviolet, to mid-infrared regions. In this solar spectrum range, the average absorption is greater than 90%. In addition, the spectral absorption is 97.69%, 96.35%, 94.45%, and 96.11% in the respective solar spectrum regions, respectively. In this work, we observed the highest absorption response of the solar spectrum. Further, the KNN regressor model is employed for behavior prediction of the proposed absorber structure and results indicate this model highly predicts the absorption values for lower K values. This proposed model due to its ideal characteristics can be employed for a vast range of applications including performance improvement of solar cells, thermophotovoltaics, and many more.

Keywords

• KNN Regressor
• Solar Energy
• Absorption
• Solar spectrum
• Machine Learning
• Optimization