排灌机械工程学报2024，Vol.42Issue(1)：8-13,6.DOI:10.3969/j.issn.1674-8530.22.0088
基于改进引力搜索算法的水轮机调节系统仿真
Simulation of hydraulic turbine regulation system based on improved gravitational search algorithm
摘要
Abstract
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.关键词
水轮机调节系统/改进引力搜索算法/PID参数优化/粒子群算法Key words
hydraulic turbine governing system/improved gravitational search algorithm/PID parameter optimization/particle swarm optimization algorithm分类
农业科技引用本文复制引用
潘虹,杭晨阳,郑源..基于改进引力搜索算法的水轮机调节系统仿真[J].排灌机械工程学报,2024,42(1):8-13,6.基金项目
国家重点研发计划政府间国际科技创新合作重点专项(2019YFE0105200) （2019YFE0105200）
国家自然科学基金资助项目(51809082) （51809082）
