Optimal operation via a recurrent neural network of a wind-solar energy system

This paper focuses on the optimal operation of a wind-solar energy system, interconnected to the utility grid; moreover, it incorporates batteries for energy storing and supplying, and an electric car. It presents a neural network optimization approach combined with a multi-agent system (MAS). The objective is to determine the optimal amounts of power for wind, solar, and batteries, including the one of the electric car, in order to minimize the amount of energy to be provided by the utility grid. Simulation results illustrate that generation levels for each energy source can be reached in an optimal form using the proposed method.