Optimal Allocation of Inertia for Renewable Energy Sources to Improve System Frequency Stability

Incorporating virtual inertia control in renewable energy sources can enhance the operational safety and stability of the system. However, the dynamic characteristics of different renewable energy sources, like wind turbines and photovoltaic units, differ significantly, vary greatly. This paper presents an optimal allocation strategy for inertia in renewable energy sources to maximize their inertia support capabilities. Firstly, a system frequency response (SFR) model incorporating virtual inertia control is developed. Subsequently, the joint debugging of MATLAB and Simulink is used to extract the virtual inertia control coefficients within the SFR model as the optimal objects. The optimal goal is to minimize the sum of control coefficients for each renewable energy unit, leading to the formulation of a mathematical optimal model. Secondly, the genetic algorithm is employed to address the mathematical model, and then input optimized coefficients into the SFR model for simulation by joint debugging. The optimal allocation scheme of virtual inertia is determined through iterative adjustments until the frequency quantization indexes satisfy the system's safe operational criteria. Finally, the proposed scheme's effectiveness is confirmed in the modified four-machine, two-zone system. The results indicate that the optimal allocation scheme of inertia can effectively improve the frequency response capability of renewable energy sources.