基于蚁群算法自整定PID的风电系统最大风能追踪研究
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(中国矿业大学 信息与电气工程学院,江苏 徐州 221008)

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孙 伟(1963-),男,江苏徐州人,教授,博士生导师,主要从事智能控制与应用,优化控制算法,复杂工业过程控制方向的研究。[FQ)]

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Study on Maximum Wind Energy Tracking Based on Ant Colony Optimization of Self-tuning PID
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(School of Information and Electrical Engineering, China University of Mine and Technology, Xuzhou 221008, China)[JZ)]

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    摘要:

    针对风力发电系统处于欠功率阶段时,风能利用系数须保持在最大值的问题,以欠功率阶段的最大风能追踪为研究重点,对风力机捕获风能的过程进行理论分析,提出了一种基于蚁群算法自整定PID的最大风能追踪控制策略,利用蚁群算法的全局优化能力优化PID的3个参数,给出了该算法的基本思想以及具体实现步骤,设计了蚁群算法自整定PID控制器,搭建了系统仿真图,并对其进行相应的仿真分析;仿真结果表明,与传统的PID控制策略相比,该控制策略使控制系统具有良好的动态响应能力,提高了风电系统的控制精度、风能利用率、输出功率,实现了机组的优化运行。

    Abstract:

    In view of problem that power coefficient must keep maximum value when wind power system is in underpower stage, based on the maximum wind power tracking in under power stage as the research key, analysed the theory on the process of wind turbine to capture wind energy. The paper proposed a control stategy of maximum wind power tracking based on ant colony optimization of self-tuning PID, used global optimization capability of ant colony algorithm to optimize three parameters of PID. The basic idea of the algorithm and the specific implementation steps was given and self-tuning PID controller based on ant colony algorithm was designed. Build the system simulation diagram to do corresponding simulation analysis. The simulation results shows that the proposed control strategy made the control system has good dynamic performance, improved control accuracy, wind energy utilization rate and output power. Which realized optimal running of wind turbines.

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孙伟,张明伟,李停,陈杨,亢国栋.基于蚁群算法自整定PID的风电系统最大风能追踪研究计算机测量与控制[J].,2015,23(1):110-112.

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  • 在线发布日期: 2015-03-27
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