Restructuration of distribution power system using Genetics Algorithms

Sebaa, Karim; Henini, Noureddine; Tlemçani, Abdelhalim; Nouri, Hassan

doi:10.1109/upec.2015.7339834

Cited by 1 publication

(2 citation statements)

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“…The limitation with the work is that the ideal of manual reconfiguration is scantly reported in literature and the procedural steps taken were tedious as in switch repositioning and further integration of DGs [33]. Sebaa et al (2015) presented application of GAfor the reconfiguration of the distribution power system to minimize loses, improve the load-ability and the voltage profile. A typical real distribution system of 106 bus of Algeria was used as test case system.…”

Section: 0mentioning

confidence: 99%

“…It was observed the new topology obtained brought appreciable reduction in real power loss, improves the system loadability and enhance the system voltage profile significantly. However, the major drawback as pointed by the work is that GA exhibit long computational time before convergence and is due to searching on the unfeasible region [34] Gurjar, Mewada, and Desai (2015) presented grid reconfiguration via GA and NSGA-II. The major shortcoming of GA is that it fails to find solution when multiple objectives are to be optimized aside being too time consuming, hence NSGA-II was proposed to overcome these challenges.…”

Section: 0mentioning

confidence: 99%

See 1 more Smart Citation

Application of Genetic Algorithm to Network Feeder Reconfiguration in Radial Distribution System

Ajenikoko¹,

Ajenikoko²,

Adedoyin³

et al. 2018

IJASTR

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Distribution system being the final link in the hierarchical structure of power system is expanding daily due to exponential growth in man's activities that require power supply for its function. The fidelity of distribution system to faithfully accounts for energy obtained is highly hampered by the losses occurring at this end. It is reported that distribution system alone account for 13% of the total loss in power system. In view of this, power system engineers are faced with the challenges of minimizing the loss, reducing voltage deviation and maintaining system topology. One of the most cost effective means of doing this is network feeder reconfiguration which harnessed the feature of distribution system. Network reconfiguration re-positions the status of sectionalizing the tie-switches with a view to minimize real power losses, reduce voltage deviation and maintain network topology. This paper presents application of genetic algorithm to network feeder reconfiguration in radial distribution system. The motivation of picking GA is not unconnected with its ability to handle ill-structured optimization problems effectively. Samples of relevant papers were reviewed from 2010 till date, it was discovered that several variants of GA has emerged, alongside with hybridized version of GA. The modification(s) made and improvement on the original GA has been carefully presented. In all, the summary of improvement on GA on this concept revolved around codification methods, adaptive operators, and changes in fitness functions.It is hoped that this piece of work will be found useful to those working or intend working on distribution network reconfiguration using GA.

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Section: 0mentioning

confidence: 99%

Section: 0mentioning

confidence: 99%