Please use this identifier to cite or link to this item: https://scholar.ptuk.edu.ps/handle/123456789/506
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dc.contributor.authorBadran, Ola-
dc.contributor.authorMokhlis, Hazlie-
dc.contributor.authorMekhilef, Saad-
dc.contributor.authorDahalan, Wardiah-
dc.date.accessioned2019-05-18T10:39:01Z-
dc.date.available2019-05-18T10:39:01Z-
dc.date.issued2017-07-20-
dc.identifier.citationhttps://link.springer.com/journal/13369en_US
dc.identifier.urihttps://scholar.ptuk.edu.ps/handle/123456789/506-
dc.description.abstractNetwork reconfiguration is a well-known technique for the distribution system to reduce power losses. However, the reconfiguration technique, by itself, could only minimize power losses up to a certain point. Further power losses reduction could be realized via the application of distributed generation (DG). However, the integration of DG to the distribution system at a non-optimal value could instead increase power losses and voltage fluctuation. Therefore, it is vital to develop an effective optimization strategy to determine the optimal output of the DG and simultaneously ensure optimal configuration. This paper presents a simultaneous optimal network reconfiguration with optimal DG output to minimize power losses and improve the voltage profile. Different objectives are discussed in this paper: (1) to minimize power losses, (2) to improve voltage profile index, (3) to maximize DG output. Evolutionary programming, particle swarm optimization, firefly, and gravitational search algorithm methods have been applied for optimal distribution network reconfiguration with optimal DG output. To evaluate the possibilities of the suggested method, simulations using MATLAB software are carried out on an IEEE 33-bus radial distribution system. The obtained outcomes prove the efficiency of the proposed strategy to find an optimal network configuration and optimal output of DG unitsen_US
dc.publisherArabian Journal for Science and Engineeringen_US
dc.titleMulti-Objective Network Reconfiguration with Optimal DG Output Using MetaHeuristic Search Algorithmsen_US
dc.typeBook chapteren_US
Appears in Collections:Engineering and Technology Faculty

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