摘要
针对抽水蓄能机组工况之间频繁转换、常规比例-积分-微分控制(proportional-integral-derivative control,PID)控制对不同工况变化下适应性弱及现有的新型控制方法难以应用于实时性要求较高的可编程逻辑控制器(programmable logic controller,PLC)调速系统中等问题,同时考虑到导数分量易引入高频测量噪声。结合模糊控制理论,创新地提出了一种以水头和功率作为模糊推理输入变量的新型自适应模糊PI控制器(innovative adaptive fuzzy PI,IAFPI)。首先结合所设计的控制器建立了基于弹性水击和对数投影曲线法的抽水蓄能调节系统精细化模型;然后利用多目标粒子群算法(multiple objective particle swarm optimization,MOPSO)优化该模型的控制参数;最后结合我国某实际抽水蓄能电站数据,分别与传统PI、传统模糊PI控制在不同负荷不同水头下进行对比仿真试验;验证所设计的新型自适应模糊PI控制器可有效提高机组对工况变化的自适应性。
In response to the issues of frequent transitions between operating conditions in pumped storage units,the limited adaptability of conventional PID control to varying operating conditions,and the challenges of applying existing advanced control methods to real-time demanding PLC speed control systems,the potential introduction of high-frequency measurement noise associated with derivative components further complicates the situation.The innovative Adaptive Fuzzy PI controller(IAFPI)was proposed in this study,incorporating fuzzy control theory,with water head and power as fuzzy inference input variables.The refined model of the pumped storage regulation system,based on the elastic water hammer and logarithmic projection curve method,was initially established in this study in conjunction with the designed controller.Subsequently,the control parameters of this model were optimized using the Multiple Objective Particle Swarm Optimization(MOPSO)algorithm.Finally,by utilizing data from an actual pumped storage power plant in China,comparative simulation experiments are conducted under different loads and heads to compare the IAFPI controller with traditional PI control and conventional fuzzy PI control,
作者
冯陈
刘朝爽
吴春旺
郑源
FENG Chen;LIU Chaoshuang;WU Chunwang;ZHENG Yuan(School of Energy and Electrical Engineering,Hohai University,Nanjing 211100,Jiangsu Province,China;NARI Water Conservancy and Hydropower Technology Co.,Ltd.,Nanjing 211106,Jiangsu Province,China;School of Energy and Environment,Southeast University,Nanjing 211189,Jiangsu Province,China)
出处
《电网技术》
EI
CSCD
北大核心
2024年第7期2815-2822,I0053-I0055,共11页
Power System Technology
基金
国家自然科学基金(青年基金)项目(52209110)
中央高校基本科研业务费专项资金项目(B220202005)
中国博士后科学基金(面上基金)项目(2022M711017)。
关键词
抽蓄机组调节系统
PI控制
模糊控制
自适应控制
多目标粒子群算法
控制优化
pumped storage unit governing system
PI control
fuzzy control
adaptive control
multiple objective particle swarm optimization
control optimization
