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首页> 外文期刊>International journal of electrical and power engineering >Stochastic Particle Swarm Optimizaion for Tuning of PID Controller in Load Frequency Control of Single Area Reheat Thermal Power System
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Stochastic Particle Swarm Optimizaion for Tuning of PID Controller in Load Frequency Control of Single Area Reheat Thermal Power System

机译：单区再热火电系统负荷频率控制中PID控制器整定的随机粒子群算法

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摘要

This study investigates the stability and optimum gain settings of Load Frequency Control (LFC) for single area reheat thermal power system. The new Particle Swarm Optimization technique (PSO) is used for optimizing Proportional Integral Differential (PID) controller gain values. The proposed technique can be used for the design of the proper PID controller for load frequency control with the help of different objective functions. Furthermore, extension to the uncertainties in the plant model parameters case is also included to illustrate the effectiveness of the proposed controller in damping power system oscillations that follow disturbances. The uncertainties in the plant model parameters case are emulated by changing turbine time constant, generator time constant, reheater time constant and speed regulator parameters by ±25%. Finally, the enhancement in the dynamic response of the system is verified through simulation results of a system under different operating points and exposed to both small and large disturbances. Time domain analysis is used to demonstrate, the necessity of the proposed controller in suppressing power system oscillations that follow disturbances.
机译：本研究调查了单区域再热火电系统负载频率控制（LFC）的稳定性和最佳增益设置。新的粒子群优化技术（PSO）用于优化比例积分微分（PID）控制器增益值。所提出的技术可用于设计适当的PID控制器，以借助不同的目标函数进行负载频率控制。此外，还包括对工厂模型参数情况下不确定性的扩展，以说明所提出的控制器在抑制跟随扰动的电力系统振荡中的有效性。通过将涡轮机时间常数，发电机时间常数，再热器时间常数和调速器参数更改±25％，可以模拟工厂模型参数情况下的不确定性。最终，通过系统在不同工作点下的仿真结果验证了系统动态响应的增强，并且该仿真结果受到大小干扰。时域分析用于证明所提出的控制器在抑制跟随扰动的电力系统振荡中的必要性。

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