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Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms

Owing to the acute shortage of electric power in the majority of countries, short-term measures such as installation of Distributed Generators (DGs) have attracted much attention in recent decades. Employment of DGs can provide numerous advantages for the power systems through reduction of losses, e...

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Main Authors: Mirsaeidi, Sohrab, Li, Shangru, Devkota, Subash, He, Jinghan, Li, Meng, Wang, Xiaojun, Konstantinou, Charalambos, Mat Said, Dalila, Muttaqi, Kashem M.
Format: Article
Published: Korean Institute of Electrical Engineers 2022
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/103092/
http://dx.doi.org/10.1007/s42835-022-01080-9
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spelling my.utm.1030922023-10-12T09:26:38Z http://eprints.utm.my/103092/ Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms Mirsaeidi, Sohrab Li, Shangru Devkota, Subash He, Jinghan Li, Meng Wang, Xiaojun Konstantinou, Charalambos Mat Said, Dalila Muttaqi, Kashem M. TK Electrical engineering. Electronics Nuclear engineering Owing to the acute shortage of electric power in the majority of countries, short-term measures such as installation of Distributed Generators (DGs) have attracted much attention in recent decades. Employment of DGs can provide numerous advantages for the power systems through reduction of losses, escalation of the voltage profile, as well as mitigation of pollutant emissions. However, in case they are not optimally allotted, they may even lead to aggravation of the network operation from different aspects. The aim of this paper is to explore the optimal size and location of DGs using metaheuristic optimization algorithms so that the network performance is enhanced. The salient feature of the proposed strategy compared to the previous works is that it contemplates optimal allotment of DGs under various objectives, i.e. minimization of total network active and reactive power losses, and Cumulative Voltage Deviation (CVD), with different weight values. Furthermore, the impact of enhancement in the number of DGs on different aspects of power system performance is investigated. Finally, to increase the accuracy of the results, three different nature-inspired optimization algorithms, i.e. Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), and Particle Swarm Optimization (PSO) are deployed, and their speed in approaching the global optimum is compared with each other. The simulation results on IEEE 14-bus system indicate that the proposed strategy not only can reinforce the overall network performance through reduction of active and reactive power losses, and voltage deviation but also lead to the improvement of network voltage profile. Korean Institute of Electrical Engineers 2022 Article PeerReviewed Mirsaeidi, Sohrab and Li, Shangru and Devkota, Subash and He, Jinghan and Li, Meng and Wang, Xiaojun and Konstantinou, Charalambos and Mat Said, Dalila and Muttaqi, Kashem M. (2022) Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms. Journal of Electrical Engineering and Technology, 17 (n/a). pp. 2617-2630. ISSN 1975-0102 http://dx.doi.org/10.1007/s42835-022-01080-9 DOI: 10.1007/s42835-022-01080-9
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mirsaeidi, Sohrab
Li, Shangru
Devkota, Subash
He, Jinghan
Li, Meng
Wang, Xiaojun
Konstantinou, Charalambos
Mat Said, Dalila
Muttaqi, Kashem M.
Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms
description Owing to the acute shortage of electric power in the majority of countries, short-term measures such as installation of Distributed Generators (DGs) have attracted much attention in recent decades. Employment of DGs can provide numerous advantages for the power systems through reduction of losses, escalation of the voltage profile, as well as mitigation of pollutant emissions. However, in case they are not optimally allotted, they may even lead to aggravation of the network operation from different aspects. The aim of this paper is to explore the optimal size and location of DGs using metaheuristic optimization algorithms so that the network performance is enhanced. The salient feature of the proposed strategy compared to the previous works is that it contemplates optimal allotment of DGs under various objectives, i.e. minimization of total network active and reactive power losses, and Cumulative Voltage Deviation (CVD), with different weight values. Furthermore, the impact of enhancement in the number of DGs on different aspects of power system performance is investigated. Finally, to increase the accuracy of the results, three different nature-inspired optimization algorithms, i.e. Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), and Particle Swarm Optimization (PSO) are deployed, and their speed in approaching the global optimum is compared with each other. The simulation results on IEEE 14-bus system indicate that the proposed strategy not only can reinforce the overall network performance through reduction of active and reactive power losses, and voltage deviation but also lead to the improvement of network voltage profile.
format Article
author Mirsaeidi, Sohrab
Li, Shangru
Devkota, Subash
He, Jinghan
Li, Meng
Wang, Xiaojun
Konstantinou, Charalambos
Mat Said, Dalila
Muttaqi, Kashem M.
author_facet Mirsaeidi, Sohrab
Li, Shangru
Devkota, Subash
He, Jinghan
Li, Meng
Wang, Xiaojun
Konstantinou, Charalambos
Mat Said, Dalila
Muttaqi, Kashem M.
author_sort Mirsaeidi, Sohrab
title Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms
title_short Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms
title_full Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms
title_fullStr Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms
title_full_unstemmed Reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms
title_sort reinforcement of power system performance through optimal allotment of distributed generators using metaheuristic optimization algorithms
publisher Korean Institute of Electrical Engineers
publishDate 2022
url http://eprints.utm.my/103092/
http://dx.doi.org/10.1007/s42835-022-01080-9
_version_ 1781777643843092480
score 13.211869

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