Parameter Identification of Asynchronous Load Nodes

Author:

Kryukov Andrey12,Suslov Konstantin23ORCID,Ilyushin Pavel34ORCID,Akhmetshin Azat5

Affiliation:

1. Department of Transport Electric Power, Irkutsk State Transport University, 664074 Irkutsk, Russia

2. Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia

3. Department of Hydropower and Renewable Energy, National Research University “Moscow Power Engineering Institute”, 111250 Moscow, Russia

4. Department of Research on the Relationship between Energy and the Economy, Energy Research Institute of the Russian Academy of Sciences, 117186 Moscow, Russia

5. Department of Power Engineering, Kazan State Power Engineering University, 420066 Kazan, Russia

Abstract

Asynchronous loads (AL), because of their low negative-sequence resistance, produce the effect of reduced unbalance at their connection points. Therefore, proper modeling of unbalanced load flows in power supply systems requires properly accounting for AL. Adequate models of the induction motor can be realized in the phase frame of reference. The effective use of such models is possible only if accurate data on the parameters of induction motor equivalent circuits for positive and negative sequences are available. Our analysis shows that the techniques used to determine these parameters on the basis of reference data can yield markedly disparate results. It is possible to overcome this difficulty by applying parameter identification methods that use the phase frame of reference. The paper proposes a technique for parameter identification of models of individual induction motors and asynchronous load nodes. The results of computer-aided simulation allow us to conclude that by using parameter identification, we can obtain an equivalent model of an asynchronous load node, and such a model provides high accuracy for both balanced and unbalanced load flow analysis. By varying load flow parameters, we demonstrate that the model proves valid over a wide range of their values. We have proposed a technique for the identification of asynchronous load nodes with such asynchronous loads, including electrical drives equipped with static frequency converters. With the aid of the AL identification models proposed in this paper, it is possible to solve the following practical tasks of management of electric power systems: increasing the accuracy of modeling their operating conditions; making informed decisions when taking measures to reduce unbalance in power grids while accounting for the balancing adjustment effect of AL.

Funder

Conducting applied scientific research

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference26 articles.

1. Identification of three-phase induction motor parameters in the case when initial values of estimates vary in a wide range;Afanasyev;Power Eng. Res. Equip. Technol.,2015

2. Experimental study of efficacy of the technique of adaptive identification of electrical parameters of the induction machine with an open-circuit rotor winding under steady-state conditions on the basis of the power balance;Rakov;Elektrotekhnicheskie I Inf. Kompleks. I Sist.,2022

3. Online parameter identification of the equivalent circuit and control of load stability;Nagaitsev;Nauchnye Probl. Transp. Sib. I DAL’NEGO Vost.,2015

4. Khemliche, M., Latreche, S., and Khellaf, A. (2004, January 21–24). Modelling and identification of the asynchronous machine. Proceedings of the First International Symposium on Control, Communications and Signal Processing 2004, Hammamet, Tunisia.

5. Model calibration strategy for energy-efficient operation of induction machines;Janisch;IFAC-PapersOnLine,2022

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3