With the increasing number of devices and the advent of 5G and 6G networks, ensuring reliable power and data connectivity remains a significant challenge, particularly in rural or remote areas. Simultaneous Wireless Information and Power Transfer (SWIPT) networks have emerged as a promising solution to power devices without batteries. However, their deployment in real-world scenarios is hindered by complex channel conditions and spatial dynamics. This research introduces a two-tier analytical model grounded in stochastic geometry, where base stations (BSs) are arranged along roads following a Poisson Line Cox Process (PLCP), while user equipment (UEs) is distributed using a Poisson Point Process (PPP). A comparative evaluation against planar PPP-based models demonstrates the performance advantages of this novel approach. Additionally, a Genetic Algorithm (GA) is applied to explore real-world scenario parameters, enhancing the model's adaptability and performance in practical applications.