Optimization of Control Strategy in Synchronous Generator Excitation System

Synchronous generator is the core power supply unit of power system, and its operation stability directly determines the safety and reliability of power supply. As the key control component of synchronous generator, the excitation system aims to maintain stable terminal voltage, regulate reactive power distribution, and enhance the transient operation stability of the system. With the construction of new power system and the implementation of the "dual-carbon" goal, large-scale renewable energy such as wind power and photovoltaic power is connected to the grid, resulting in strong nonlinearity, time-varying parameters and frequent disturbances in power system operation. Traditional excitation control strategies can no longer meet the requirements of high-precision and high-robustness control. Taking the excitation system of synchronous generator as the research object, this paper systematically constructs the mathematical model of excitation system, analyzes the inherent defects of classical PID control and constant voltage control, and designs three advanced control strategies: fuzzy PID control, sliding mode variable structure control and model predictive control. A simulation platform is built via MATLAB/Simulink, and performance comparison is carried out under three working conditions: steady-state operation, load step and power grid short-circuit fault. The results show that model predictive control has the best steady-state control accuracy and the fastest dynamic response; fuzzy PID control balances engineering practicability and control performance; sliding mode variable structure control owns the strongest robustness. The research results provide theoretical support and technical reference for the engineering optimization design of synchronous generator excitation system, and are of great practical significance for improving the safe and stable operation of new power systems.