Hybrid Model Predictive Control with Adaptive Modulation for Voltage Balancing in Three-Phase Three-Level NPC Rectifiers for Green Hydrogen Production

Abstract

This paper proposes a hybrid model predictive control (HMPC) strategy for a three-level neutral-point-clamped (3L NPC) rectifier to optimize the operation of electrolyzers for green hydrogen production. Unlike conventional approaches that focus primarily on inverter applications, the proposed method directly addresses the critical issue of neutral-point voltage imbalance in NPC rectifiers. The control framework combines discrete switching-state selection with adaptive objective prioritization, utilizing real-time capacitor voltage measurements to exploit switching-state redundancy. A multi-objective cost function balances current tracking, DC-link voltage regulation, neutral-point voltage balancing, and switching-loss minimization. An adaptive weighting mechanism dynamically prioritizes control objectives in response to system conditions such as renewable intermittency and grid disturbances. To improve long-term reliability, the strategy introduces state diversity enforcement and inactivity penalties, reducing capacitor stress without compromising harmonic performance. The effectiveness of the proposed method is evaluated using a dynamic equivalent model of a proton exchange membrane (PEM) electrolyzer, enabling a realistic assessment of green hydrogen production. Validation through hardware in the loop (HIL) test demonstrates robust current control and stable DC-link voltages in varying operating scenarios.