基于改进引力搜索算法的水轮机调节系统仿真OACSTPCD

In response to the current challenges faced by hydropower units,such as multiple complex operating conditions and limitations in engineering calculations due to algorithm complexity,an im-proved gravitational search algorithm(improved PSOGSA)was proposed to enhance the optimization performance of hydraulic turbine control parameters and address the shortcomings of traditional control strategies in meeting dynamic demands.Firstly,combined with the PSO algorithm,a learning factor was introduced into the velocity update formula of GSA for improvement.Secondly,a weighting coeffi-cient was applied to optimize the position update formula to enhance the algorithm's adaptability.Final-ly,combined with relevant simulation modeling experiments,the proposed improved PSOGSA was uti-lized to optimize the PID parameters of the hydraulic turbine regulation system.The simulation results demonstrate that,when subjected to a 5%no-load frequency disturbance,the improved PSOGSA PID controller is significantly superior to the conventional algorithm mentioned above.The regulated model system achieves stability within a shorter time period,and its overshoot at this time is much lower than that of conventional algorithms.These findings indicate that the improved PSOGSA exhibits higher ite-ration efficiency in subsequent iterations,and improves the problem of easily converging to local opti-mum in conventional algorithms.Thus,the reasonable and effectiveness of the improved PSOGSA are validated,and control effect of the hydraulic turbine regulating system is optimized to a certain extent.