Managing the Energy flow of a Self-Sustaining Multisource System through intelligent Management Techniques utilizing Artificial Intelligence

This paper proposes an efficient strategy for energy control in the isolated micro grid, comprising photovoltaic and wind power systems with battery storage systems. This strategy presents smart energy management (SEM) based on artificial intelligence techniques (AIT) such as the fuzzy logic controller (FLC). The SEM is designed to manage energy flows throughout the isolated micro grid, by extracting the maximum available energy during deviating constraints such as temperature, solar irradiance and wind speed, while maintaining energy quality and autonomy to meet charging requirements and ensure precise control of the battery's state of charge (SOC) over five states (Very High: SOCV.H, High: SOCH, Medium: SOCM, Low SOCL and Very Low SOC
V.L
) during charge and discharge. This is a significant improvement over traditional management systems that rely on two SOC states, namely SOC
min
and SOC
max
. Response behaviors are described and visualized in MATLAB Simulink.