Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability

This paper presents optimal multi-criteria reconfiguration of radial distribution systems with solar and wind renewable energy sources using the weight factor method while considering reliability. Minimizing the power loss, improving the voltage profile and stability of the system, as well as, enhan...

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Main Authors: Jafar-Nowdeh A., Babanezhad M., Arabi-Nowdeh S., Naderipour A., Kamyab H., Abdul-Malek Z., Ramachandaramurthy V.K.
Other Authors: 57218602027
Format: Article
Published: Elsevier B.V. 2023
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spelling my.uniten.dspace-251822023-05-29T16:07:11Z Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability Jafar-Nowdeh A. Babanezhad M. Arabi-Nowdeh S. Naderipour A. Kamyab H. Abdul-Malek Z. Ramachandaramurthy V.K. 57218602027 35110863800 55568406500 36677578000 55355146400 57195728805 6602912020 This paper presents optimal multi-criteria reconfiguration of radial distribution systems with solar and wind renewable energy sources using the weight factor method while considering reliability. Minimizing the power loss, improving the voltage profile and stability of the system, as well as, enhancing the reliability are the main objective functions of the problem to address. The reliability index is assumed as the energy not-supplied (ENS) of the end-users. Optimized variables of the problem include opened lines of the system in the reconfiguration process to maintain the radial structure of the network along with finding the optimal place and size of photovoltaic (PV) systems and wind turbine (WT) units in the distribution system, which are determined based on a new meta-heuristic called moth�flame optimization (MFO) algorithm. Simulations for different scenarios are performed utilizing reconfiguration and placement of renewable sources on an IEEE 33-bus radial distribution system. Obtained results in solving the problem indicate the superiority of the presented method compared with some methods in the literature. Furthermore, the results showed that the combined method as the reconfiguration and WT placement simultaneously bring the best performance for the network with lower power loss, improved voltage profile and stability, and enhanced reliability. Moreover, the results showed that considering reliability helps significantly reduce the energy not-supplied of the customers and supply their maximum load demand. � 2020 Elsevier B.V. Final 2023-05-29T08:07:11Z 2023-05-29T08:07:11Z 2020 Article 10.1016/j.eti.2020.101118 2-s2.0-85089745738 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089745738&doi=10.1016%2fj.eti.2020.101118&partnerID=40&md5=9f9daf72699db8cb73f909424eec92b7 https://irepository.uniten.edu.my/handle/123456789/25182 20 101118 Elsevier B.V. Scopus
institution Universiti Tenaga Nasional
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description This paper presents optimal multi-criteria reconfiguration of radial distribution systems with solar and wind renewable energy sources using the weight factor method while considering reliability. Minimizing the power loss, improving the voltage profile and stability of the system, as well as, enhancing the reliability are the main objective functions of the problem to address. The reliability index is assumed as the energy not-supplied (ENS) of the end-users. Optimized variables of the problem include opened lines of the system in the reconfiguration process to maintain the radial structure of the network along with finding the optimal place and size of photovoltaic (PV) systems and wind turbine (WT) units in the distribution system, which are determined based on a new meta-heuristic called moth�flame optimization (MFO) algorithm. Simulations for different scenarios are performed utilizing reconfiguration and placement of renewable sources on an IEEE 33-bus radial distribution system. Obtained results in solving the problem indicate the superiority of the presented method compared with some methods in the literature. Furthermore, the results showed that the combined method as the reconfiguration and WT placement simultaneously bring the best performance for the network with lower power loss, improved voltage profile and stability, and enhanced reliability. Moreover, the results showed that considering reliability helps significantly reduce the energy not-supplied of the customers and supply their maximum load demand. � 2020 Elsevier B.V.
author2 57218602027
author_facet 57218602027
Jafar-Nowdeh A.
Babanezhad M.
Arabi-Nowdeh S.
Naderipour A.
Kamyab H.
Abdul-Malek Z.
Ramachandaramurthy V.K.
format Article
author Jafar-Nowdeh A.
Babanezhad M.
Arabi-Nowdeh S.
Naderipour A.
Kamyab H.
Abdul-Malek Z.
Ramachandaramurthy V.K.
spellingShingle Jafar-Nowdeh A.
Babanezhad M.
Arabi-Nowdeh S.
Naderipour A.
Kamyab H.
Abdul-Malek Z.
Ramachandaramurthy V.K.
Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability
author_sort Jafar-Nowdeh A.
title Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability
title_short Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability
title_full Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability
title_fullStr Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability
title_full_unstemmed Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability
title_sort meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability
publisher Elsevier B.V.
publishDate 2023
_version_ 1806427546122715136
score 13.214268