Analysis of Load Frequency Control using Extended Kalman filter and Linear Quadratic Regulator based controller

Vishwas Vasuki Gautam, Renuka Loka, A. M. Parimi
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引用次数: 2

Abstract

Increasing power demands for sustenance cause power systems to receive multiple load disturbances rapidly, leading to variations in the system frequencies, thus making Load Frequency Control (LFC) one of the critical research areas in power system operation. One solution is the Linear Quadratic Regulator (LQR) based feedback controller for LFC that computes the optimal feedback gain values from the known system parameters and state variables by minimizing a cost function. However, all the system parameters and state variables may not be available at all times, which restricts the use of the LQR controller. Therefore, the proposed estimation algorithm, i.e., the Extended Kalman filter (EKF), is utilized to estimate the state variables using a series of measurements over time. The simulation results produced using the EKF-LQR-based controller validate that the proposed scheme can efficiently regulate the system frequency and offer robust performance compared to Virtual Synchronous Generator-based (VSG) and conventional PID controllers.
基于扩展卡尔曼滤波和线性二次型调节器的负荷频率控制分析
随着电力需求的不断增加,电力系统会迅速受到多重负荷干扰,从而导致系统频率的变化,因此负荷频率控制(load Frequency Control, LFC)成为电力系统运行的关键研究领域之一。一种解决方案是基于线性二次调节器(LQR)的LFC反馈控制器,该控制器通过最小化成本函数,从已知的系统参数和状态变量计算最优反馈增益值。然而,并非所有的系统参数和状态变量在任何时候都可用,这限制了LQR控制器的使用。因此,提出的估计算法,即扩展卡尔曼滤波(EKF),利用一系列随时间的测量来估计状态变量。基于ekf - lqr控制器的仿真结果表明,与基于虚拟同步发电机(VSG)和传统PID控制器相比,该控制器可以有效地调节系统频率,并具有鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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