Power Routing Algorithms: A Comparative Study

Abstract

Energy internet is a new development stage of the smart grid that aims to reduce reliance on the main grid, boost the use of green energy, raise energy efficiency, and decrease the size and cost of the energy storage system. Energy routers (ERs), which control data and power flows, are used to transfer energy between parties. The power routing problem seeks to identify the best path between energy consumers and producers, in a graph with each link consisting of two nodes (ERs). The path with the lowest power losses is selected among the available paths. This paper presents a novel distributed power routing algorithm inspired by the Q-learning approach with both low computational cost and reduced communication overhead. This algorithm is validated through a comparative study with various power routing techniques, including the shortest path algorithm, graph traversal algorithm, and metaheuristic algorithms. Through MATLAB simulation, the performance of these algorithms is analyzed based on the power losses and computational effort.