Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System

Modern power systems are confronted with operational challenges that increase the risk of transient instability. Existing Dynamic Security Assessment (DSA) tools have limitations, necessitating accurate and timely assessment of transient stability. To address this, a novel approach for real-time ide...

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Main Authors: Sarmin M.K.N.M., Saadun N., Azmi M.T., Abidin I.Z.
Other Authors: 56177713500
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2024
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spelling my.uniten.dspace-343702024-10-14T11:19:20Z Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System Sarmin M.K.N.M. Saadun N. Azmi M.T. Abidin I.Z. 56177713500 55612145600 56340771500 35606640500 cascading analysis hardware-in-the-loop simulation linear state estimation performance index phasor measurement unit Transient stability Data Analytics Electric power system interconnection Electric power system protection Energy management systems Hardware-in-the-loop simulation Learning systems Real time systems State estimation Synthetic apertures System stability Wide area networks Cascading analyse Hardwarein-the-loop simulations (HIL) Linear state estimation Operating condition Operational challenges Performance indices Power Real- time Time transient Transient instability Phasor measurement units Modern power systems are confronted with operational challenges that increase the risk of transient instability. Existing Dynamic Security Assessment (DSA) tools have limitations, necessitating accurate and timely assessment of transient stability. To address this, a novel approach for real-time identification of transient instability is introduced in this paper using a Thevenin equivalent network model. The proposed method leverages synchronized phasor measurements and incorporates PMU-based Energy Management System (EMS) with Linear State Estimation (LSE) alongside snapshots from existing EMS systems, cascading analysis application, and a performance index (PI) to rank cascading outages based on severity. A case study demonstrates the effectiveness of the proposed method to identify transient instabilities in a large interconnected power system through real-time hardware-in-the-loop (HIL) simulations. By offering enhanced accuracy and efficiency in real-time stability assessment, the method empowers grid operators to promptly act and prevent wide area outages during challenging operating conditions. Future research directions encompass integration with Wide-Area Monitoring, Protection, and Control (WAMPAC) system, incorporation of advanced machine learning techniques alongside data analytics, as well as scalability examination across diverse operating conditions and contingencies. � 2023 IEEE. Final 2024-10-14T03:19:20Z 2024-10-14T03:19:20Z 2023 Conference Paper 10.1109/I-PACT58649.2023.10434732 2-s2.0-85187012400 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187012400&doi=10.1109%2fI-PACT58649.2023.10434732&partnerID=40&md5=7921c56779a421f00c9b36fdf0be6f9e https://irepository.uniten.edu.my/handle/123456789/34370 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic cascading analysis
hardware-in-the-loop simulation
linear state estimation
performance index
phasor measurement unit
Transient stability
Data Analytics
Electric power system interconnection
Electric power system protection
Energy management systems
Hardware-in-the-loop simulation
Learning systems
Real time systems
State estimation
Synthetic apertures
System stability
Wide area networks
Cascading analyse
Hardwarein-the-loop simulations (HIL)
Linear state estimation
Operating condition
Operational challenges
Performance indices
Power
Real- time
Time transient
Transient instability
Phasor measurement units
spellingShingle cascading analysis
hardware-in-the-loop simulation
linear state estimation
performance index
phasor measurement unit
Transient stability
Data Analytics
Electric power system interconnection
Electric power system protection
Energy management systems
Hardware-in-the-loop simulation
Learning systems
Real time systems
State estimation
Synthetic apertures
System stability
Wide area networks
Cascading analyse
Hardwarein-the-loop simulations (HIL)
Linear state estimation
Operating condition
Operational challenges
Performance indices
Power
Real- time
Time transient
Transient instability
Phasor measurement units
Sarmin M.K.N.M.
Saadun N.
Azmi M.T.
Abidin I.Z.
Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System
description Modern power systems are confronted with operational challenges that increase the risk of transient instability. Existing Dynamic Security Assessment (DSA) tools have limitations, necessitating accurate and timely assessment of transient stability. To address this, a novel approach for real-time identification of transient instability is introduced in this paper using a Thevenin equivalent network model. The proposed method leverages synchronized phasor measurements and incorporates PMU-based Energy Management System (EMS) with Linear State Estimation (LSE) alongside snapshots from existing EMS systems, cascading analysis application, and a performance index (PI) to rank cascading outages based on severity. A case study demonstrates the effectiveness of the proposed method to identify transient instabilities in a large interconnected power system through real-time hardware-in-the-loop (HIL) simulations. By offering enhanced accuracy and efficiency in real-time stability assessment, the method empowers grid operators to promptly act and prevent wide area outages during challenging operating conditions. Future research directions encompass integration with Wide-Area Monitoring, Protection, and Control (WAMPAC) system, incorporation of advanced machine learning techniques alongside data analytics, as well as scalability examination across diverse operating conditions and contingencies. � 2023 IEEE.
author2 56177713500
author_facet 56177713500
Sarmin M.K.N.M.
Saadun N.
Azmi M.T.
Abidin I.Z.
format Conference Paper
author Sarmin M.K.N.M.
Saadun N.
Azmi M.T.
Abidin I.Z.
author_sort Sarmin M.K.N.M.
title Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System
title_short Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System
title_full Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System
title_fullStr Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System
title_full_unstemmed Real-Time Transient Instability Identification in Power Systems using a PMU-Based EMS System
title_sort real-time transient instability identification in power systems using a pmu-based ems system
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2024
_version_ 1814061052857417728
score 13.211869