Performance Study of Load Power Management and Control based on ANN and MPC for Standalone PV-Battery DC Off-Microgrid

In this paper, a Load Power Management (LPM) Strategy, Artificial Neural Network (ANN) and Model Predictive Control (MPC) are developed for a standalone DC off-microgrid based on Photovoltaic (PV) system and Battery Energy System (BES). The State of Charge (SoC) of the BES and the generated power from the PV, are used as inputs for the LPM The connected loads are classified into three categories with different priorities, where the LPM manages the loads by disconnecting and reconnecting them to ensure uninterruptible power supply to the selected critical loads. Furthermore, an ANN is employed to achieve MPPT from the PV system, and the MPC is used to regulate the voltage and control the current of the BES. The performance of the proposed system and its control strategies are evaluated using Matlab/Simulink simulation.