Multi-objective optimization study on operating parameters of hydrogenerator based on genetic algorithm

The efficient operation of hydrogenerator is essential for improving energy utilization and ensuring system reliability. This paper proposes a multiobjective optimization approach for hydrogenerator operating parameters based on a genetic optimization algorithm. The method simultaneously considers multiple performance objectives, including enhancing generation efficiency, reducing vibration amplitude, and minimizing mechanical losses. An improved genetic algorithm with adaptive crossover and mutation mechanisms is developed to accelerate convergence and maintain population diversity. An experimental model of a hydrogenerator unit is established to evaluate the proposed optimization framework. The results indicate that the optimized operating parameters lead to a notable improvement in overall efficiency and stability compared with traditional manual adjustment methods. The results in this paper demonstrate that the genetic algorithm-based multiobjective optimization strategy provides an effective and practical solution for real-time control and performance optimization of hydrogenerator systems.