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 time-varying loads, can lead to high total harmonic distortion (THD) and distorted output waveforms of voltage and current. To address these issues, a hierarchical control method with enhanced speed and comprehensiveness for both primary and secondary levels is required. In this paper, a fast model predictive optimization algorithm is introduced as the primary control method to predict operational states in advance, maintain low THD, and thereby reduce its impact on power quality. Subsequently, a secondary switching control is incorporated to correct the frequency and power allocation deviations introduced by the primary control, restore the microgrid voltage and frequency to their rated values, and ensure stable reactive power. Finally, simulation and comparative results demonstrate the effectiveness and applicability of the proposed method.