Integration of artificial neural networks for multi-source energy management in a smart grid

Eziitouni Jarmouni (Hassan First University of Settat)
Ahmed Mouhsen (Hassan First University of Settat)
Mohammed Lamhammedi (Hassan First University of Settat)
Hicham Ouldzira (Hassan First University of Settat)

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol 12, No 3: September 2021

Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.