Real-time inertia estimation via ARMAX model representation and synchrophasor measurements

IF 1.3 4区工程技术 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Latin America Transactions Pub Date : 2025-04-22 DOI:10.1109/TLA.2025.10974367

Alexander Sanchez-Ocampo;Mario R. Arrieta Paternina;Jose M. Ramos-Guerrero;Gabriel E. Mejia-Ruiz;Juan M. Ramirez-Arredondo;Lucas Lugnani;Felix Munguia-Perez;Alejandro Zamora-Mendez;Juan R. Rodriguez-Rodriguez

{"title":"Real-time inertia estimation via ARMAX model representation and synchrophasor measurements","authors":"Alexander Sanchez-Ocampo;Mario R. Arrieta Paternina;Jose M. Ramos-Guerrero;Gabriel E. Mejia-Ruiz;Juan M. Ramirez-Arredondo;Lucas Lugnani;Felix Munguia-Perez;Alejandro Zamora-Mendez;Juan R. Rodriguez-Rodriguez","doi":"10.1109/TLA.2025.10974367","DOIUrl":null,"url":null,"abstract":"This paper introduces the real-time implementation with the actual hardware architecture environment (HAE) of an online estimation method that tracks the equivalent time-varying inertia in power systems. The proposed method enables automated and accurate inertia estimation, exploiting the ARMAX model representation and the Teager-Kaiser energy operator (TKEO) disturbance time detector. The effectiveness and high accuracy of the proposed framework are successfully validated in laboratory conditions with actual synchronised measurements from Phasor Measurement Units (PMUs) over a real-time emulated New England 39-bus system. The estimate is achieved with a relative error ranging from 0.1% to 7%, even under noisy conditions and atypical measurement values. The literature reviewed does not report any estimation method that is more accurate than the one proposed in this work.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 5","pages":"405-414"},"PeriodicalIF":1.3000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10974367","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Latin America Transactions","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10974367/","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

This paper introduces the real-time implementation with the actual hardware architecture environment (HAE) of an online estimation method that tracks the equivalent time-varying inertia in power systems. The proposed method enables automated and accurate inertia estimation, exploiting the ARMAX model representation and the Teager-Kaiser energy operator (TKEO) disturbance time detector. The effectiveness and high accuracy of the proposed framework are successfully validated in laboratory conditions with actual synchronised measurements from Phasor Measurement Units (PMUs) over a real-time emulated New England 39-bus system. The estimate is achieved with a relative error ranging from 0.1% to 7%, even under noisy conditions and atypical measurement values. The literature reviewed does not report any estimation method that is more accurate than the one proposed in this work.

查看原文本刊更多论文

实时惯性估计通过ARMAX模型表示和同步量测量

本文介绍了一种电力系统等效时变惯性在线估计方法在实际硬件环境下的实时实现。该方法利用ARMAX模型表示和Teager-Kaiser能量算子（TKEO）扰动时间检测器实现了自动准确的惯性估计。在实验室条件下，通过实时仿真新英格兰39总线系统上相量测量单元（pmu）的实际同步测量，成功验证了所提出框架的有效性和高精度。即使在噪声条件和非典型测量值下，估计的相对误差也在0.1%至7%之间。文献综述没有报告任何估计方法比在这项工作中提出的更准确。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Latin America Transactions COMPUTER SCIENCE, INFORMATION SYSTEMS-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

3.50

自引率

7.70%

发文量

192

审稿时长

3-8 weeks

期刊介绍： IEEE Latin America Transactions (IEEE LATAM) is an interdisciplinary journal focused on the dissemination of original and quality research papers / review articles in Spanish and Portuguese of emerging topics in three main areas: Computing, Electric Energy and Electronics. Some of the sub-areas of the journal are, but not limited to: Automatic control, communications, instrumentation, artificial intelligence, power and industrial electronics, fault diagnosis and detection, transportation electrification, internet of things, electrical machines, circuits and systems, biomedicine and biomedical / haptic applications, secure communications, robotics, sensors and actuators, computer networks, smart grids, among others.