A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System

A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System

In this paper, a model reference controller (MRC) based on a neural network (NN) is proposed for damping oscillations in electric power systems. Variation in reactive load, internal or external perturbation/faults, and asynchronization of the connected machine cause oscillations in power systems. If...

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Main Authors: Waqar Uddin, Nadia Zeb, Kamran Zeb, Muhammad Ishfaq, Imran Khan, Saif Ul Islam, Ayesha Tanoli, Aun Haider, Hee-Je Kim, Gwan-Soo Park
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Energies
Subjects:
power oscillations
UPFC
non-linear control
neural network
model reference control
Online Access:https://www.mdpi.com/1996-1073/12/19/3653
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spelling doaj-eb46589b8ec6493db0c5ea9f026cf3f62020-11-25T02:16:14ZengMDPI AGEnergies1996-10732019-09-011219365310.3390/en12193653en12193653A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power SystemWaqar Uddin0Nadia Zeb1Kamran Zeb2Muhammad Ishfaq3Imran Khan4Saif Ul Islam5Ayesha Tanoli6Aun Haider7Hee-Je Kim8Gwan-Soo Park9School of Electrical and Computer Engineering, Pusan National University, 2 Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan-city-46241, KoreaDepartment of Electrical Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22010, PakistanSchool of Electrical and Computer Engineering, Pusan National University, 2 Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan-city-46241, KoreaSchool of Electrical and Computer Engineering, Pusan National University, 2 Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan-city-46241, KoreaSchool of Electrical and Computer Engineering, Pusan National University, 2 Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan-city-46241, KoreaSchool of Electrical and Computer Engineering, Pusan National University, 2 Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan-city-46241, KoreaDepartment of Electrical Engineering, University of Management and Technology, Lahore, Sialkot Campus, Sialkot 51040, PakistanDepartment of Electrical Engineering, University of Management and Technology, Lahore, Sialkot Campus, Sialkot 51040, PakistanSchool of Electrical and Computer Engineering, Pusan National University, 2 Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan-city-46241, KoreaSchool of Electrical and Computer Engineering, Pusan National University, 2 Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan-city-46241, KoreaIn this paper, a model reference controller (MRC) based on a neural network (NN) is proposed for damping oscillations in electric power systems. Variation in reactive load, internal or external perturbation/faults, and asynchronization of the connected machine cause oscillations in power systems. If the oscillation is not damped properly, it will lead to a complete collapse of the power system. An MRC base unified power flow controller (UPFC) is proposed to mitigate the oscillations in 2-area, 4-machine interconnected power systems. The MRC controller is using the NN for training, as well as for plant identification. The proposed NN-based MRC controller is capable of damping power oscillations; hence, the system acquires a stable condition. The response of the proposed MRC is compared with the traditionally used proportional integral (PI) controller to validate its performance. The key performance indicator integral square error (ISE) and integral absolute error (IAE) of both controllers is calculated for single phase, two phase, and three phase faults. MATLAB/Simulink is used to implement and simulate the 2-area, 4-machine power system.https://www.mdpi.com/1996-1073/12/19/3653power oscillationsUPFCnon-linear controlneural networkmodel reference control
collection DOAJ
language English
format Article
sources DOAJ
author Waqar Uddin
Nadia Zeb
Kamran Zeb
Muhammad Ishfaq
Imran Khan
Saif Ul Islam
Ayesha Tanoli
Aun Haider
Hee-Je Kim
Gwan-Soo Park
spellingShingle Waqar Uddin
Nadia Zeb
Kamran Zeb
Muhammad Ishfaq
Imran Khan
Saif Ul Islam
Ayesha Tanoli
Aun Haider
Hee-Je Kim
Gwan-Soo Park
A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System
Energies
power oscillations
UPFC
non-linear control
neural network
model reference control
author_facet Waqar Uddin
Nadia Zeb
Kamran Zeb
Muhammad Ishfaq
Imran Khan
Saif Ul Islam
Ayesha Tanoli
Aun Haider
Hee-Je Kim
Gwan-Soo Park
author_sort Waqar Uddin
title A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System
title_short A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System
title_full A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System
title_fullStr A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System
title_full_unstemmed A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System
title_sort neural network-based model reference control architecture for oscillation damping in interconnected power system
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-09-01
description In this paper, a model reference controller (MRC) based on a neural network (NN) is proposed for damping oscillations in electric power systems. Variation in reactive load, internal or external perturbation/faults, and asynchronization of the connected machine cause oscillations in power systems. If the oscillation is not damped properly, it will lead to a complete collapse of the power system. An MRC base unified power flow controller (UPFC) is proposed to mitigate the oscillations in 2-area, 4-machine interconnected power systems. The MRC controller is using the NN for training, as well as for plant identification. The proposed NN-based MRC controller is capable of damping power oscillations; hence, the system acquires a stable condition. The response of the proposed MRC is compared with the traditionally used proportional integral (PI) controller to validate its performance. The key performance indicator integral square error (ISE) and integral absolute error (IAE) of both controllers is calculated for single phase, two phase, and three phase faults. MATLAB/Simulink is used to implement and simulate the 2-area, 4-machine power system.
topic power oscillations
UPFC
non-linear control
neural network
model reference control
url https://www.mdpi.com/1996-1073/12/19/3653
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