Latency and Energy Transmission Cost Optimization using BCO-aware Energy Routing for Smart Grid

In recent years the Smart Grids also known as intelligent energy systems have attracted the attention of researchers and became an active area for research. Smart Grid (SG) is a new development stage of power systems that aims to increase the efficiency of the energy transmission, to balance the demand and supply in the network and to improve the use of the distributed renewable energy sources. Since the transmitted energy have some losses in transmission path, which is the major issue in energy routing protocols. Where the main question is how to decrease the energy transmission loss in other words, how to find the efficient energy transmission path with the minimum transmission cost. Different methods and protocols have been proposed to solve the energy transmission path problem. These proposed protocols are based on traditional methods such as graph theory, game theory, autonomous systems, consensus... etc. In this paper, we have considered the problem of determining the energy efficient path as an optimization problem. In order to solve this problem, we proposed the use of swarm optimization methods in particularly the Bee Colony Optimization method. We have used the principle of bee foraging behaviour and proposed an energy routing protocol based on BCO algorithm to determine the lowest cost and latency energy path using features of power transmission and peer to peer energy market in smart grids.