Control-Oriented Design of a Standalone PV-Battery-Inverter System with Dynamic Load

Abstract

Maintaining voltage stability in photovoltaic-based power systems is often challenged by variable solar input and dynamic load profiles. This paper presents a Simulink-based simulation of a PV-battery system in which a Model Predictive Control (MPC) strategy is employed to regulate the DC bus voltage with high precision. The system consists of a PV array connected via a boost converter governed by a Maximum Power Point Tracking (MPPT) algorithm, and a battery energy storage system interfaced through a non-isolated bidirectional converter. The proposed MPC algorithm actively manages the bidirectional converter by predicting system behaviour and optimizing control actions in real time, ensuring that the DC bus voltage is maintained consistently at 48V despite changing generation and consumption conditions. To evaluate performance under realistic operating scenarios, the system is tested with various load conditions, including nonlinear and time-varying loads. Unlike conventional PID-based control, the MPC approach offers faster dynamic response, better handling of system constraints, and improved overall stability. An inverter connected to the DC bus supplies a single-phase AC load, completing the system. Simulation results validate the effectiveness of the proposed control architecture in achieving reliable voltage regulation, efficient power sharing, and enhanced resilience against operational disturbances.