Two-Level Hierarchical Control of a PV-Battery Hybrid Energy System using Differential Flatness-Based Strategy and MShOA-Tuned FOPID Controller

Abstract

This work provides a two-level hierarchical control for a hybrid energy system (HES) composed of a photovoltaic (PV) source and a battery bank connected to a DC bus. The primary-level controller is based on a differential flatness strategy, which offers optimal energy balancing between the PV source, the battery, and the load by generating accurate reference current trajectories. The secondary-level controller is a Fractional Order PID (FOPID) controller whose parameters are tuned using the Mantis Shrimp Optimization Algorithm (MShOA), which is a recent bio-inspired metaheuristic optimization. This inner loop is responsible for the real-time regulation of the DC bus voltage by accurately tracking the current reference signals. The MATLAB/Simulink simulation results under dynamic load conditions validate the effectiveness of the proposed approach and demonstrate improved performance compared to conventional methods