Game Theory and Hybrid Genetic Algorithm for Energy Management and Real Time Pricing in Smart Grid
The smart grid, in broad terms, can be regarded as a complex system encompassing advanced power control, communication and computing technologies. This system includes interconnected microgrids that can draw energy from renewable and non renewable sources. Considering the intermittent nature of renewable energy sources, it might be difficult for the microgrids to constantly accommodate all the consumers connected to them. Therefore, complexity of the future smart energy systems arises from the multiplicity of interacting players operating as independent decision makers with autonomous behaviors, attitudes and goals. In this context, this paper is an overview concerning the potential of applying Game Theory in the development of a real time pricing game and a mechanism of energy management in a free electricity market, where several independent electricity suppliers will coexist. This work proposes a model of power exchange based on a Game Theory and a new Hybrid Genetic Algorithm to compute the Nash Equilibrium. We will prove that our algorithm optimizes real time cost of power, and energy losses.
2018 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM)