An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing

In this paper, an improved Non-dominated Sorting Genetic Algorithm III (NSGA III) is proposed in determining the location and sizing of multi-DGs. NSGA III is the new variant of pareto-based evolutionary algorithm by using reference point approach. Grey Relational Analysis (GRA) is used to determine...

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Main Authors: Norainon, Mohamed, Dahaman, Ishak
Format: Conference or Workshop Item
Language:English
English
Published: Springer Science and Business Media Deutschland GmbH 2022
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/39600/
http://umpir.ump.edu.my/id/eprint/39600/1/An%20Improved%20Non-dominated%20Sorting%20Genetic%20Algorithm.pdf
http://umpir.ump.edu.my/id/eprint/39600/2/An%20improved%20non-dominated%20sorting%20genetic%20algorithm%20III%20with%20grey%20relational%20analysis%20decision%20making%20for%20DG%20placement%20and%20sizing_ABS.pdf
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author Norainon, Mohamed
Dahaman, Ishak
author_facet Norainon, Mohamed
Dahaman, Ishak
author_sort Norainon, Mohamed
building UMP Institutional Repository
collection Online Access
description In this paper, an improved Non-dominated Sorting Genetic Algorithm III (NSGA III) is proposed in determining the location and sizing of multi-DGs. NSGA III is the new variant of pareto-based evolutionary algorithm by using reference point approach. Grey Relational Analysis (GRA) is used to determine the best compromise among the non-dominated pareto solutions. Considering that minimization of power losses and improvement of voltage profile as the objectives, the proposed method is applied to IEEE 14 bus system. The obtained results are comprehensively compared with other published works. From this comparative analysis, it is proved that the proposed algorithm is very effective in reducing the line losses and improving the voltage profile.
first_indexed 2025-11-15T03:34:51Z
format Conference or Workshop Item
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institution Universiti Malaysia Pahang
institution_category Local University
language English
English
last_indexed 2025-11-15T03:34:51Z
publishDate 2022
publisher Springer Science and Business Media Deutschland GmbH
recordtype eprints
repository_type Digital Repository
spelling ump-396002023-12-11T04:49:54Z http://umpir.ump.edu.my/id/eprint/39600/ An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing Norainon, Mohamed Dahaman, Ishak T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering In this paper, an improved Non-dominated Sorting Genetic Algorithm III (NSGA III) is proposed in determining the location and sizing of multi-DGs. NSGA III is the new variant of pareto-based evolutionary algorithm by using reference point approach. Grey Relational Analysis (GRA) is used to determine the best compromise among the non-dominated pareto solutions. Considering that minimization of power losses and improvement of voltage profile as the objectives, the proposed method is applied to IEEE 14 bus system. The obtained results are comprehensively compared with other published works. From this comparative analysis, it is proved that the proposed algorithm is very effective in reducing the line losses and improving the voltage profile. Springer Science and Business Media Deutschland GmbH 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39600/1/An%20Improved%20Non-dominated%20Sorting%20Genetic%20Algorithm.pdf pdf en http://umpir.ump.edu.my/id/eprint/39600/2/An%20improved%20non-dominated%20sorting%20genetic%20algorithm%20III%20with%20grey%20relational%20analysis%20decision%20making%20for%20DG%20placement%20and%20sizing_ABS.pdf Norainon, Mohamed and Dahaman, Ishak (2022) An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing. In: Lecture Notes in Electrical Engineering; 11th International Conference on Robotics, Vision, Signal Processing and Power Applications, RoViSP 2021 , 5-6 April 2021 , Virtual, Online. pp. 772-778., 829 LNEE (272139). ISSN 1876-1100 ISBN 978-981168128-8 (Published) https://doi.org/10.1007/978-981-16-8129-5_118
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Norainon, Mohamed
Dahaman, Ishak
An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing
title An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing
title_full An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing
title_fullStr An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing
title_full_unstemmed An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing
title_short An improved non-dominated sorting genetic algorithm III with grey relational analysis decision making for DG placement and sizing
title_sort improved non-dominated sorting genetic algorithm iii with grey relational analysis decision making for dg placement and sizing
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/39600/
http://umpir.ump.edu.my/id/eprint/39600/
http://umpir.ump.edu.my/id/eprint/39600/1/An%20Improved%20Non-dominated%20Sorting%20Genetic%20Algorithm.pdf
http://umpir.ump.edu.my/id/eprint/39600/2/An%20improved%20non-dominated%20sorting%20genetic%20algorithm%20III%20with%20grey%20relational%20analysis%20decision%20making%20for%20DG%20placement%20and%20sizing_ABS.pdf