Analysis and Fuzzy Neural Networks-Based Inertia Coefficient Adjustment Strategy of Power Converters

With the development of new energy generation technology and power electronic technology, power electronic equipment occupies an increasing proportion of the power system, and its control flexibility makes the power system complicated, bringing problems such as low inertia, low damping, high harmonics, low reliability, and weak anti-interference ability. Especially the influence of converter on inertia of power system, even causing excessive frequency fluctuations, leading to the collapse of the power system. In view of the inertia problem of converters, this article starts with the principle of converters and analyzes the inertia transmission characteristics of different types of converters in power systems by three types of control strategies. Based on the influence of the inertia parameters of converters on system frequency and power, a converter inertia target function is established, and a neural network adaptive adjustment strategy for converter inertia coefficient is proposed to achieve self-adaptive optimization of converter output power and system frequency. The corresponding converter model is established, and the simulation circuit and control model are built by Simulink to verify the inertia transfer characteristics. The simulation results show the correctness of the relevant theories and provide theoretical support for the inertia design of high-proportion power electronic systems.