PERFORMANCE ANALYSIS OF GEOGRAPHIC AND SELF-ORGANIZING ROUTING PROTOCOLS FOR WIRELESS MESH NETWORKS IN SMART GRID APPLICATIONS

The transition from conventional power grids to smart grids marks a major shift in energy management, with advanced communication networks playing a crucial role in supporting grid reliability and efficiency. This research addresses the communication challenges within Neighborhood Area Networks (NAN) of Smart Grid Communication Networks (SGCN), focusing on Geographic Routing Protocols—Greedy Perimeter Stateless Routing (GPSR) and Routing Protocol for Low-Power and Lossy Networks (RPL). Both protocols are proposed as promising options for smart microgrids, which require resilient, low-latency communication for optimized grid performance and effective response to dynamic conditions. Existing literature highlights the benefits and limitations of these protocols but lacks comprehensive evaluations in settings characterized by high traffic, varying shadowing, and frequent node failures, presenting a gap that this study aims to address. A simulation-based methodology is used to analyze GPSR and RPL under various operational scenarios, including stable conditions, high shadowing, increased traffic, and node failures. The simulation environment was MATLAB, where scenarios with both fixed and dynamic channel conditions were modeled to observe real-world network behaviors. The simulations focused on key performance indicators such as Packet Delivery Ratio (PDR), delay, and hop count, with model validation performed against expected theoretical outcomes. This approach provided a detailed analysis of protocol adaptability and efficiency in real-timesmart grid environments, identifying critical factors influencing the reliability and robustness of communication in NANs. The results demonstrate that while GPSR excels in low-complexity routing due to its stateless structure, it struggles with high-frequency traffic and shadowing scenarios, leading to decreased packet success rates under load. Conversely, RPL’s structured routing and tree-based architecture enable more consistent performance across scenarios, including in high-traffic conditions. RPL’s adaptability to environmental variables also results in higher packet delivery reliability and enhanced delay management, though its higher signaling demands affect computational load. Both protocols display resilience, yet RPL shows a clear advantage in environments with fluctuating conditions and stringent QoS requirements. This research contributes valuable insights into the application of GPSR and RPL for NAN communication in smart grids. By clarifying performance outcomes for these protocols under stress, the findings guide the development of more efficient, reliable SGCNs suitable for diverse microgrid applications, including dynamic load management, and distributed energy resource integration. This work supports the optimization of smart grid communication infrastructures, making significant strides towards resilient, and energy-efficient NAN deployments in the energy landscape.