Multi-agent system based on fuzzy control and prediction using NN for smart microgrid energy management

Nowadays, renewable energy is a promising solution to reduce the emissions and feed the lack of the energy in the world, the smart microgrid (MG) can be assumed as the ideal way to integrate with a large scale the renewable and clean energy source in the production of electricity and give to the consumer the opportunity to participate in the electricity market not just like consumer but also like producer, the aim of this paper is to present an energy management supervision for the MG, this management is based on multi-agent system(MAS), this concept allows the possibility to the different generation units of smart MG to collaborate in order to achieve the optimal strategy to deal with the problem of economical exchange with the main grid, The goal of our MAS is to control the amount of power delivered or taken from the main grid in order to reduce the cost and maximize the benefit, to achieve the mentioned goal we will use the neural network to predict the amount of electricity that will be produced for the next hour and fuzzy logic control for the battery to taking a reasonable decision about storing or selling electricity, finally we will show in the simulation based JADE platform the impact of using the energy management supervision.