The transition towards sustainable energy systems is critically dependent on the reliable integration of renewable energy sources into the power grid. With the increasing penetration of renewable generation, hybrid grid-connected systems comprising grid-following (GFL) and grid-forming (GFM) converters have become essential in modern power stations. This paper addresses a key challenge to sustainable grid operation: maintaining stability and power delivery during grid faults. When faults cause voltage sags at the point of common coupling (PCC), different low-voltage ride-through (LVRT) strategies significantly impact both the voltage support capability and the active power transmission capacity, which are vital for a stable and resilient energy supply. To address this, the paper proposes a coordinated LVRT strategy for GFL/GFM converters that adapts to varying grid requirements, thereby promoting sustainable grid integration. First, the topology and control strategies of the hybrid system are briefly described. The conventional LVRT control strategies for both GFL and GFM converters are then improved. Based on the severity of the grid voltage sag, the converters’ active and reactive power output are adaptively adjusted. This dual-function approach not only effectively limits fault currents, protecting sensitive equipment, but also prioritizes the continuous transmission of active power, thereby minimizing the loss of renewable generation during faults and supporting grid stability. Subsequently, through an analysis of the voltage and active power characteristics of different LVRT modes, a coordinated strategy is designed. Unlike single-converter LVRT control, the proposed method flexibly selects and adjusts control modes to meet specific grid code requirements, ensuring robust voltage support and maximizing the utilization of clean energy even under adverse conditions. Finally, the effectiveness of this coordinated control strategy in ensuring a sustainable and resilient grid connection is validated through MATLAB R2022b/Simulink simulations.
Zhang et al. (Thu,) studied this question.
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