Mean-Filtering-Based Memory Event-Triggered Overload-Avoiding Secondary Voltage Consensus Control for Microgrids

This article presents a novel secondary voltage consensus control framework for microgrids equipped with multiple distributed generators. The framework ensures that these units consistently achieve specified performance levels while demonstrating resilience to abnormal voltage signals. First, an innovative overload-avoiding performance transformation method is proposed. This approach confines the synchronization errors of all generators within prescribed performance boundaries without imposing restrictions on their initial voltage conditions. In addition, a mean-filtering-based memory event-triggered mechanism is developed to bolster the robustness of the secondary voltage control process against non-real-time signals, while also mitigating undesirable voltage fluctuations that may occur in microgrids by utilizing stored stable data. It is shown that the generators' output voltages accurately track the desired reference voltage, with the tracking performance strictly adhering to the prescribed performance criteria. Simulation results further validate the efficacy of the proposed method.