Accurate estimation of the optical properties of nanofluids for solar energy harvesting using the null-collision forward Monte Carlo method

Abstract

Nanofluid is commonly used in solar energy systems for its excellent physical properties. Its optical properties play an important role in enhancing the performance of the solar energy system. To obtain the optical properties of nanofluids accurately, we proposed a measurement technique as the combination of the null-collision forward Monte Carlo (NC-FMC) and the covariance matrix adaptation evolution strategy based on a restart strategy. An energy partition branch and a criterion are introduced to improve the performance of the classic NC-FMC. A multi-angle model is developed for alleviating the ill-posedness of the model by analyzing the confidence intervals for the estimated parameters. Numerical experiments of several nanofluids with different particle diameters and base fluids are operated to analyze the accuracy and efficiency of the measurement model. A normalized merit function is applied to test the proposed model's ability to predict the performance of a PV/T system with additional nanofluids. The results show that the proposed measurement method has good accuracy and robustness when applied to forecast the performance of PV/T system.