Modeling and Fault Characteristics Analysis of Multi-Energy Complementary Microgrids

To promote the achievement of the ’dual carbon’ goals and address the threats posed by the uncertainties of new energy sources to grid operation, it is urgent to study the operational characteristics of multi-energy microgrids that include wind, solar, and storage systems. The doubly-fed induction generator (DFIG) is the mainstream model for wind energy utilization due to its wider speed regulation range and higher energy conversion efficiency. The stator is directly linked to the grid, while the rotor excitation voltage is supplied by converters connected on both the rotor side and the grid side. This configuration enables variable speed constant frequency operation through converter control. This paper first proposes the control approach for the converters: the grid-side converter (GSC) maintains a constant DC capacitor voltage with good dynamic response capability, while the rotor-side converter (RSC) controls the speed to achieve maximum power tracking of wind energy. To improve the wind turbine's fault ride-through capability, a new crowbar protection strategy is proposed for the rotor side by incorporating the instantaneous rotor current, system voltage, and a fixed time delay as key features. Secondly, the control strategy for the photovoltaic power generation system inverter is studied, also adopting maximum power tracking to achieve efficient energy utilization. Then, a control strategy for the storage battery as the main control micro-source is proposed: during grid-connected operation, fixed active and reactive power output is used; during islanded operation, droop control is employed to maintain the stability of the microgrid's voltage and frequency. To ensure a seamless transition from isolated operation to grid-connected operation, a synchronization module is integrated into the battery storage control system. Subsequently, a microgrid model is developed using Matlab/Simulink to simulate the complementary operational characteristics of various micro-sources and the seamless transition of the microgrid operational mode. This process verifies the accuracy and effectiveness of the model.