Design of fractional evolutionary processing for reactive power planning with FACTS devices

Design of fractional evolutionary processing for reactive power planning with FACTS devices

Abstract Reactive power dispatch is a vital problem in the operation, planning and control of power system for obtaining a fixed economic load expedition. An optimal dispatch reduces the grid congestion through the minimization of the active power loss. This strategy involves adjusting the transform...

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Autores principales: Yasir Muhammad, Rizwan Akhtar, Rahimdad Khan, Farman Ullah, Muhammad Asif Zahoor Raja, J. A. Tenreiro Machado
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/3a573fe61ba74bcd8cc46f1b6cb612aa
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spelling oai:doaj.org-article:3a573fe61ba74bcd8cc46f1b6cb612aa2021-12-02T15:22:56ZDesign of fractional evolutionary processing for reactive power planning with FACTS devices10.1038/s41598-020-79838-22045-2322https://doaj.org/article/3a573fe61ba74bcd8cc46f1b6cb612aa2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-79838-2https://doaj.org/toc/2045-2322Abstract Reactive power dispatch is a vital problem in the operation, planning and control of power system for obtaining a fixed economic load expedition. An optimal dispatch reduces the grid congestion through the minimization of the active power loss. This strategy involves adjusting the transformer tap settings, generator voltages and reactive power sources, such as flexible alternating current transmission systems (FACTS). The optimal dispatch improves the system security, voltage profile, power transfer capability and overall network efficiency. In the present work, a fractional evolutionary approach achieves the desired objectives of reactive power planning by incorporating FACTS devices. Two compensation arrangements are possible: the shunt type compensation, through Static Var compensator (SVC) and the series compensation through the Thyristor controlled series compensator (TCSC). The fractional order Darwinian Particle Swarm Optimization (FO-DPSO) is implemented on the standard IEEE 30, IEEE 57 and IEEE 118 bus test systems. The power flow analysis is used for determining the location of TCSC, while the voltage collapse proximity indication (VCPI) method identifies the location of the SVC. The superiority of the FO-DPSO is demonstrated by comparing the results with those obtained by other techniques in terms of measure of central tendency, variation indices and time complexity.Yasir MuhammadRizwan AkhtarRahimdad KhanFarman UllahMuhammad Asif Zahoor RajaJ. A. Tenreiro MachadoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-29 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Yasir Muhammad
Rizwan Akhtar
Rahimdad Khan
Farman Ullah
Muhammad Asif Zahoor Raja
J. A. Tenreiro Machado
Design of fractional evolutionary processing for reactive power planning with FACTS devices
description Abstract Reactive power dispatch is a vital problem in the operation, planning and control of power system for obtaining a fixed economic load expedition. An optimal dispatch reduces the grid congestion through the minimization of the active power loss. This strategy involves adjusting the transformer tap settings, generator voltages and reactive power sources, such as flexible alternating current transmission systems (FACTS). The optimal dispatch improves the system security, voltage profile, power transfer capability and overall network efficiency. In the present work, a fractional evolutionary approach achieves the desired objectives of reactive power planning by incorporating FACTS devices. Two compensation arrangements are possible: the shunt type compensation, through Static Var compensator (SVC) and the series compensation through the Thyristor controlled series compensator (TCSC). The fractional order Darwinian Particle Swarm Optimization (FO-DPSO) is implemented on the standard IEEE 30, IEEE 57 and IEEE 118 bus test systems. The power flow analysis is used for determining the location of TCSC, while the voltage collapse proximity indication (VCPI) method identifies the location of the SVC. The superiority of the FO-DPSO is demonstrated by comparing the results with those obtained by other techniques in terms of measure of central tendency, variation indices and time complexity.
format article
author Yasir Muhammad
Rizwan Akhtar
Rahimdad Khan
Farman Ullah
Muhammad Asif Zahoor Raja
J. A. Tenreiro Machado
author_facet Yasir Muhammad
Rizwan Akhtar
Rahimdad Khan
Farman Ullah
Muhammad Asif Zahoor Raja
J. A. Tenreiro Machado
author_sort Yasir Muhammad
title Design of fractional evolutionary processing for reactive power planning with FACTS devices
title_short Design of fractional evolutionary processing for reactive power planning with FACTS devices
title_full Design of fractional evolutionary processing for reactive power planning with FACTS devices
title_fullStr Design of fractional evolutionary processing for reactive power planning with FACTS devices
title_full_unstemmed Design of fractional evolutionary processing for reactive power planning with FACTS devices
title_sort design of fractional evolutionary processing for reactive power planning with facts devices
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/3a573fe61ba74bcd8cc46f1b6cb612aa
work_keys_str_mv AT yasirmuhammad designoffractionalevolutionaryprocessingforreactivepowerplanningwithfactsdevices
AT rizwanakhtar designoffractionalevolutionaryprocessingforreactivepowerplanningwithfactsdevices
AT rahimdadkhan designoffractionalevolutionaryprocessingforreactivepowerplanningwithfactsdevices
AT farmanullah designoffractionalevolutionaryprocessingforreactivepowerplanningwithfactsdevices
AT muhammadasifzahoorraja designoffractionalevolutionaryprocessingforreactivepowerplanningwithfactsdevices
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