Hierarchical Control of AC/DC Hybrid Microgrid Based on Primary Model Predictive Optimization and Secondary Switching Control

Abstract

The fluctuating characteristics of renewable energy generation in hybrid AC/DC microgrids, combined with timevarying loads, can result in high total harmonic distortion (THD) and distorted output voltage and current waveforms. To address these issues, a faster and more comprehensive primary and secondary hierarchical control method is required. In this paper, a faster model predictive optimization algorithm is introduced as a primary control method to predict operational states in advance, maintain a low THD state, and reduce the impact on power quality. Then, a secondary switching control is added to correct frequency and power allocation errors caused by primary control, recover microgrid voltage and frequency to their rated values, and ensure stable reactive power. Finally, simulation and comparison results prove the proposed method's effectiveness and applicability.