基于电源-硬件在环实验平台的非线性负载参数估计工作流程

Matthew R. Overlin, Christopher Smith, M. Ilic, J. Kirtley
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引用次数: 1

摘要

低惯性微电网很容易出现单负荷占总负荷大部分的情况,从而极大地影响稳定性和电能质量。本文提出了恒流负载(CILs)和恒功率负载(cpl)的动态负载模型,而不是静态负载模型。其次,采用柔性电源-硬件在环(PHiL)试验台进行实验。PHiL试验台由一台实时计算机和一个功率放大器组成,以扰动其电压和频率。连接的负载充当被测设备(DUT)。以捕获的实验数据为参考,实现了参数估计算法。得到的参数估计用于定义仿真模型。对CIL和CPL动态模型进行了仿真,产生的波形与实验波形非常相似。该算法被称为增强型蒙特卡罗算法(EMCA),在本工作中进行了解释。最后给出了EMCA的参数估计结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Workflow for Non-linear Load Parameter Estimation Using a Power-Hardware-in-the-Loop Experimental Testbed
Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of static load models, dynamic load models are presented here for constant current loads (CILs) and constant power loads (CPLs). Next, a flexible Power-Hardware-in-the-Loop (PHiL) testbed is employed for the experiments in this work. The PHiL testbed consists of a real-time computer working with a power amplifier in order to perturb its voltage and frequency. A connected load serves as the device under test (DUT). Using the captured experimental data as a reference, a parameter estimation algorithm is then implemented. The resulting parameter estimates are used to define simulation models. Both the CIL and CPL dynamic models are simulated to produce waveforms that closely resemble experimental waveforms. The algorithm, referred to as an enhanced monte carlo algorithm (EMCA), is explained in this work. Finally, the EMCA’s resulting parameter estimates are presented.
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