Genetic Algorithm-Based Path Selection for Power-Efficient Energy Routing in Smart Grids and Energy Internet

Energy routing stands out as one of the most critical challenges within energy networks. Path selection, a fundamental aspect of energy routing, poses a complex problem aimed at identifying the route with minimal power loss. Numerous studies have been conducted to solve this issue. Some of these approaches are bio-inspired, while the rest are graph theory-based, such as Dijkstra's algorithm to find the shortest path. However, many of these solutions either lack a comprehensive grasp of the complexity of energy transmission dynamics or lack scalability. This paper aims to develop an energy routing scheme for path selection in smart grids and the energy internet. We use a genetic algorithm to compute power loss and determine the optimal route for energy transfer, accounting for losses in both transmission and conversion. The algorithm explores the solution space in search of the optimal path, effectively minimizing time and space complexity. Simulation results demonstrate significant improvements over a similar existing approach, highlighting the effectiveness and efficiency of our proposed method.