Efficient Energy Routing in Smart Grid Networks Using Fractional Knapsack and Dijkstra Algorithm

Smart Grids (SG) have opened up new avenues for research, particularly in the field of energy routing. However, energy routing poses several challenges such as identifying the most efficient routes and selecting the optimal group of producers to purchase from. Although heuristic methods are currently used to address these challenges, they often fall short of delivering optimal solutions. In this paper, we propose to address both the subset selection problem and the efficient path problem in a small residential area using a greedy method. Our approach formulates the problem as a fractional knapsack problem, with the objective of maximizing energy value while considering capacity constraints. To determine the optimal routes based on their distance, we employ the Dijkstra algorithm. We then use the proposed greedy function to determine the optimal set of sellers for every consumer. Based on the simulation results, we have demonstrated the effectiveness of the proposed optimization algorithm.