The transport of nanoparticles in polymer networks has critical implications in biology and medicine, especially through thermophoresis in response to temperature gradients. This study presents a single-particle energy-conserving dissipative particle dynamics (seDPD) method by integrating a single-particle model into the energy-conserving DPD model to simulate the mesoscopic thermophoretic behavior of nanoparticles in polymer matrices. We first validate the newly developed seDPD model through comparisons with analytical solutions for nanoparticle viscosity, thermal diffusivity, and hydrodynamic drag and then demonstrate the effectiveness of the seDPD model in capturing thermophoretic forces induced by temperature gradients. The results show that nanoparticles driven by the Soret forces exhibit unique transport characteristics, such as drift velocity and diffusivity, leading to a significant acceleration of nanoparticle diffusion in the polymer network, which has been known as the giant acceleration of diffusion. Quantifying how nanoparticles move in flexible polymer networks sheds light on the interaction dynamics of nanoparticles within polymer networks, providing insight into nanoparticle behavior in complex environments that could be leveraged in various applications from drug delivery to material design.