Multi-agent architecture for smart micro-grid optimal control using a hybrid BP-PSO algorithm for wind power prediction

In this paper we present a multi-agent architecture based on wind power prediction using neural network (NN) trained by hybrid particle swarm optimization (PSO) algorithm and back-propagation algorithm,this process aims to implement smart micro-grid with different generation units like wind turbines and fuel generators. In the proposed architecture this micro-grid can exchange electricity with the main grid therefore it can buy or sell electricity. The main objective is to find the optimal policy using average wind speed prediction for the next hour in order to maximize the benefit and minimize the cost. Finally, for the simulation the JADE (Java Agent Development Framework) platform is proposed to implement the approach and analyze the results.