Alocação Ótima De Geradores Distribuídos Para Redução De Perdas Em Sistemas Elétricos De Distribuição Considerando Incertezas Da Demanda

Batista, Rodrigo Viana; Araujo, Leandro Ramos de; Penido, Débora Rosana Ribeiro

doi:10.48011/asba.v2i1.1736

Cited by 1 publication

(2 citation statements)

References 8 publications

(8 reference statements)

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“…Regarding the number of DER, in [5], 6 DER were chosen for allocation in IEEE 13, 34 and 123 node test feeders in order to ensure the greatest diversity of buses choices. In [8], tests were carried out on systems with 37 nodes test feeder, selecting 9 and 37 DER.…”

Section: Resultsmentioning

confidence: 99%

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Optimized Allocation and Sizing of Distributed Energy Resource in Distribution Systems Using Cuckoo Search Algorithm

Ferraz¹,

Ferraz²,

Rueda-Medina³

et al. 2021

XIX Conferência De Estudos Em Engenharia Elétrica

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The Distributed Energy Resources (DER) emerged as an alternative to centralized generation since it presents numerous economic and operational benefits, such as, power loss reduction, voltage profile improvement, and relieved system's congestion. These benefits can be obtained by optimized sizing and placement of the DER; however, an improper DER integration can generate problems regarding the levels of current, voltage and power factor of the network. In this paper, the Cuckoo Search (CS) metaheuristic algorithm was applied to solve the allocation and sizing problem in IEEE 13 and 34 node test feeders in order to improve the voltage profile. The results were compared with the Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) with the purpose of validating the CS method. Finally, it was possible to conclude that CS algorithm presented satisfactory results, meeting all constraints regarding the amount of DER, voltage levels and operational limits.

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Section: Resultsmentioning

confidence: 99%

“…In [5] and [6], the authors applied the Genetic Algorithms (GA) for DER allocation and sizing in order to improve the voltage profile and to reduce power losses. In [1], [7] and [8], the Particle Swarm Optimization (PSO) was used for the same purpose.…”

Section: Introductionmentioning

confidence: 99%