Skip to main content

Research Repository

Advanced Search

Extended mixed integer quadratic programming for simultaneous distributed generation location and network reconfiguration

Tami, Y.; Sebaa, K.; Lahdeb, M.; Usta, O.; Nouri, H.

Extended mixed integer quadratic programming for simultaneous distributed generation location and network reconfiguration Thumbnail


Authors

Y. Tami

K. Sebaa

M. Lahdeb

O. Usta

Profile Image

Hassan Nouri Hassan.Nouri@uwe.ac.uk
Reader in Electrical Power and Energy



Abstract

Introduction. To minimise power loss, maintain the voltage within the acceptable range, and improve power quality in power distribution networks, reconfiguration and optimal distributed generation placement are presented. Power flow analysis and advanced optimization techniques that can handle significant combinatorial problems must be used in distribution network reconfiguration investigations. The optimization approach to be used depends on the size of the distribution network. Our methodology simultaneously addresses two nonlinear discrete optimization problems to construct an intelligent algorithm to identify the best solution. The proposed work is novel in that it the Extended Mixed-Integer Quadratic Programming (EMIQP) technique, a deterministic approach for determining the topology that will effectively minimize power losses in the distribution system by strategically sizing and positioning Distributed Generation (DG) while taking network reconfiguration into account. Using an efficient Quadratic Mixed Integer Programming (QMIP) solver (IBM ®), the resulting optimization problem has a quadratic form. To ascertain the range and impact of various variables, our methodology outperforms cutting-edge algorithms described in the literature in terms of the obtained power loss reduction, according to extensive numerical validation carried out on typical IEEE 33-and 69-bus systems at three different load factors. Practical value. Examining the effectiveness of concurrent reconfiguration and DG allocation versus sole reconfiguration is done using test cases. According to the findings, network reconfiguration along with the installation of a distributed generator in the proper location, at the proper size, with the proper loss level, and with a higher profile, is effective. References 24, table 4, figures 14.

Citation

Tami, Y., Sebaa, K., Lahdeb, M., Usta, O., & Nouri, H. (2023). Extended mixed integer quadratic programming for simultaneous distributed generation location and network reconfiguration. Electrical Engineering and Electromechanics, 2023(2), 93-100. https://doi.org/10.20998/2074-272X.2023.2.14

Journal Article Type Article
Acceptance Date Dec 22, 2022
Online Publication Date Mar 5, 2023
Publication Date Mar 5, 2023
Deposit Date Mar 15, 2023
Publicly Available Date Mar 16, 2023
Journal Electrical Engineering and Electromechanics
Print ISSN 2074-272X
Electronic ISSN 2309-3404
Peer Reviewed Peer Reviewed
Volume 2023
Issue 2
Pages 93-100
Series Title Power Stations, Grids and Systems
DOI https://doi.org/10.20998/2074-272X.2023.2.14
Keywords Electrical and Electronic Engineering; Mechanical Engineering; Energy Engineering; Power Technology; active distribution networks; distribution system reconfiguration; distributed generation; mixed-integer quadratic programming; power loss
Public URL https://uwe-repository.worktribe.com/output/10554946
Publisher URL http://eie.khpi.edu.ua/article/view/265607

Files





You might also like



Downloadable Citations