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

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

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DOI/Official URL: https://doi.org/10.1007/978-981-16-8129-5_118

Abstract

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.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Line loss minimization; NSGA III; Voltage profile; Voltage stability
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	College of Engineering Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	11 Dec 2023 04:49
Last Modified:	11 Dec 2023 04:49
URI:	http://umpir.ump.edu.my/id/eprint/39600
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