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Dynamic Equivalent Modeling for Multi-Microgrid Based on Structure Preservation Method
89
Citations
28
References
2018
Year
EngineeringPower Grid OperationDistributed Energy GenerationPower ElectronicsStabilityDistributed Energy ResourcesSystems EngineeringPower System ControlGrid StabilityElectrical EngineeringDc MicrogridsComputer EngineeringElectric Grid IntegrationMicrogridsPower System DynamicSmart GridEnergy ManagementDynamic Equivalent ModelingDynamic Equivalent ModelsEigenvalue Analysis
Increasing integration of distributed energy resources in multi‑microgrids makes accurate models high‑order and unsuitable for online transient analysis. The study proposes a dynamic equivalent modeling method for inverter‑based multi‑microgrids to reduce model order. The method constructs a detailed 3‑MG model, partitions it into a study MG and external MGs, replaces the external MGs with low‑order dynamic equivalents using a structure‑preservation approach, and validates the reduced model through numerical simulation and eigenvalue analysis.
As an increasing number of distributed energy resources (DERs) are integrated in the multi-microgrid (MMG) to meet load demand, the accurate model of MMG becomes high-order and unsuitable for online transient analysis. To address this issue, a dynamic equivalent modeling method for the inverter-based MMG is presented. When focusing on the dynamic behaviors of DERs within a microgrid (MG), the external MGs do not need to be modeled in detail and can be replaced by dynamic equivalent models. At first, the detailed model of a 3-MG system with droop-controlled DERs and PQ-controlled DERs is built as an example to show the equivalent modeling procedure. Subsequently, the developed 3-MG system is partitioned into a study MG and two external MGs. The study MG of the MMG retains its accurate form, while the external MGs will be replaced by the dynamic equivalent models whose model orders are much lower than that of the original one. The proposed procedure is based on the structure preservation method without the time-consuming iterative calculation. Finally, the validation range of the proposed method is verified with different models using the numerical simulation and eigenvalue analysis.
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