Optimal allocation of DG regarding to power system security via DE technique

Estabragh, Mohsen Rezaie; Mohammadian, Mohsen

doi:10.1109/aeect.2011.6132489

Cited by 5 publications

(1 citation statement)

References 16 publications

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“…Važno je naglasiti i da ovi proračuni nisu bili ograničeni striktno na test-slučajeve, za šta se primer može naći u radu [7], u kome su se autori uhvatili u koštac sa razvojem prenosnog sistema Kolumbije, dobijajući pritom rezultate usklađene sa teorijski postavljenim predviđanjima. Pored ovoga, mora se pomenuti i rad [8], koji se bavio utilizacijom diferencijalne evolucije prilikom preciziranja optimalne lokacije distribuiranih generatorskih kapaciteta, kao i rad [9], u kome je diferencijalna evolucija adaptirana radi definisanja najboljeg mogućeg mesta za izgradnju nove transformatorske stanice u elektroenergetskom sistemu, uz primenu Geografskog Informacionog Sistema (Geographic Information System -GIS).…”

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Application of differential evolution for defining the optimal grid reinforcement shown on the test-system

Ristić¹,

Šošić²

2020

Tehnika

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Building of the renewable energy sources in the geographic areas that were not, until that moment, recognized as the locations where the energy could be generated could lead to the change in load flows and voltage values in the system in which these sources are being incorporated. The inability of the system operator to deny the connection of the renewable sources can often cause the need for the system reinforcements between the newly created productive regions and the existing zones with the significant consumption. Therefore, the goal of this paper is the determination of the optimal new line that should be commissioned in the system, according to the results of the conducted multi-criteria optimization, performed using the differential evolution method, modified applying the georeferencing principle. This calculation takes into account the maximization of the installed capacity of the connected renewable source and minimization of the energy losses ' costs in the system during the lifespan of the built line as the objective functions for optimization. The application of the developed methodology is demonstrated on the test-system containing 30 nodes, with the wind power plant being connected to the grid in one of them.

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