A Novel Digital Twin for Diesel Generator in Microgrids

Diesel generators (DiGs) play a vital role in Micro grids (MG) to ensure resiliency and reliability; however, accurate modeling of their behavior in both grid-connected and islanded modes is challenging due to limited experimental and manufacturer data. Standard simulation models often fail to capture real world dynamics, leading to inaccurate results. To address these limitations, this paper presents an adaptive digital twin (DT) model for the 62.5kVA DiG unit at the Center for Microgrid Research (CMR). The DT model, capable of grid-connected and islanded operations, is developed and experimentally validated within the CMR's Microgrid infrastructure. The proposed DT leverages a novel adaptive parameter methodology to dynamically reflect the generator's behavior in varying operating conditions for both transient and steady-state responses. The results confirm that the adaptive DT accurately replicates the dynamic response of the real-world industry-grade DiG. The DT offers a robust modeling platform for advanced MG studies that involve DiGs under multiple operation modes.