## 3 Methodology  
Power line communication is a transformative technique that reimagines power distribution lines as communication conduits. By capitalizing on existing infrastructure, PLC enables efficient and cost-effective communication within the smart grid. From advanced metering to integrating renewable energy sources and enabling demand response, PLC offers a versatile and impactful solution for modernizing the energy landscape. Its continued evolution holds the promise of a smarter, more resilient, and responsive grid that can meet the challenges of the evolving energy ecosystem. Demand response (DR) is a crucial energy management strategy that involves adjusting electricity consumption patterns in response to signals from the power grid. It plays a vital role in balancing energy supply and demand, enhancing grid stability, and optimizing the utilization of existing resources. Demand response programs empower consumers, businesses, and industries to actively participate in grid management by voluntarily curtailing or shifting their electricity usage during periods of high demand or grid stress. A smart grid significantly improves energy efficiency through the integration of advanced technologies, data-driven insights, and dynamic control mechanisms. By enhancing the monitoring, management, and coordina  
Figure 5: Migration of features via interdependence between power supply reliability and communication reliability [43].  
tion of energy generation, distribution, and consumption, a smart grid optimizes resource utilization and reduces wastage.  
Smart grids enable dynamic pricing models that reflect real-time electricity supply and demand. Consumers can adjust their energy consumption based on price signals, reducing usage during expensive periods and promoting efficiency. Smart grid technologies allow for the replacement of aging infrastructure with more efficient components. This includes upgrading transformers, substations, and transmission lines to minimize energy losses during transmission. Smart grids leverage data analytics and artificial intelligence to analyze historical consumption patterns, predict future demand, and optimize energy distribution. These insights enable informed decision-making that improves energy efficiency. Embracing artificial intelligence and predictive analytics, the smart grid anticipates load patterns, predicts congestion, and optimizes power transmission routes. Moreover, cyber-physical systems merge real-time data from internet of things (IoT) devices, enabling rapid responses to disruptions and providing insights for effective power delivery strategies. The smart grid's integration of distributed energy resources (DERs) like solar panels and wind turbines at the grid edge enhances efficiency by generating power close to consumption points, thus reducing transmission distances. Furthermore, integrated energy markets foster resource sharing across regions, optimizing power generation and transmission on a broader scale. Smart grids incorporate sensors, smart meters, and other monitoring devices throughout the system. These sensors provide real-time data on electricity consumption, grid conditions, and equipment performance. This information enables operators to make timely adjustments, optimize energy flows, and address inefficiencies promptly as shown in Figure 6.  
Figure 6: The flowchart that is being followed for this research work.  
This figure provides a visual representation of the systematic approach employed in our research methodology. Following Figure 6, clarifications for the acronyms NFVI (network function virtualization infrastructure), VMs (virtual machines), NFV (network function virtualization), MAN (metropolitan area network), WAN (wide area network), NANS (network attached network storage), EANS (enterprise access network system), and FANS (flight attendant notification system) are provided.