The primary objective of this research is to mitigate the negative impacts of active power fluctuations in weak power grids using grid-connected converters (GCCs). Weak grids need more infrastructure and stability measures to accommodate the integration of renewable energy sources, such as high levels of solar photovoltaic power. One of the key challenges encountered in such grids is the absence of inertia from converter-based resources, which can lead to grid instability. This thesis proposes a solution to this challenge by employing power electronics grid-forming converters to synthesize additional inertia and damping properties, effectively emulating the behavior of synchronous generators through the use of virtual synchronous generator (VSG)-based converter control strategies. By incorporating these control strategies, the proposed method aims to overcome the limitations of weak. Integrating high levels of solar photovoltaic power into weak grids can lead to local mode oscillations and grid instability. To tackle this issue, the proposed method focuses on suppressing these oscillations by emulating a virtual damper winding (VDE) within the VSG-based GCC. By incorporating virtual inertia and damping properties, mitigating active power fluctuations and enabling the smooth integration of solar photovoltaic power. A genetic algorithm (GA) optimization tool is introduced to optimize the VSG-based GCC’s performance. This tool allows for the optimization of virtual damping and inertia parameters, enabling the VSG-based converter to effectively adapt to the changing conditions of weak grids. Through comprehensive time-domain and frequency-domain analyses, the proposed method is evaluated, and simulation results validate the effectiveness of the optimization technique and implementation procedure. The validity of the proposed method is further confirmed through simulations conducted in the MATLAB/Simulink environment, which encompass various operating scenarios encountered in weak grids. The thesis provides a comprehensive discussion of the approach, optimization tool, and simulation results, emphasizing the efficacy of the proposed method in addressing the challenges associated with weak grids.
