Firefly algorithm based solution to minimize the real power loss in a power system

Balachennaiah, P.; Suryakalavathi, M.; Nagendra, P.

doi:10.1016/j.asej.2015.10.005

Cited by 41 publications

(25 citation statements)

References 24 publications

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“…Já Balachennaiah et al (2015) aplicaram o FA com o objetivo de minimizar a perda de potência real de uma rede de transmissão de energia. O algoritmo tem a função de otimizar variáveis como, por exemplo, a magnitude de tensão.…”

Section: Aplicações Práticas Dos Algoritmos Do Vaga-lume E Do Morcegounclassified

“…Dentre os diversos algoritmos implementados com base na inteligência de enxames, o Algoritmo do Vaga-lume (Firefly Algorithm) e o Algoritmo do Morcego (Bat Algorithm) foram, recentemente, propostos por Yang (2009) e Yang (2010), respectivamente. O Firefly Algorithm (FA) é baseado na característica de bioluminescência dos vaga-lumes e vem sendo usado para resolver problemas na área de controle de tráfego aéreo (Wang et al, 2012), de telecomunicações (Sarma & Gopi, 2014), de sistemas de potência (Balachennaiah, Suryakalavathi & Nagendra, 2015) e de muitos outros. Já o Bat Algorithm (BA) é inspirado na ecolocalização dos morcegos a qual é desempenhada durante o voo.…”

Section: Introductionunclassified

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Um Breve Estudo Sobre Os Algoritmos Dos Vaga-Lumes E Dos Morcegos Para Otimização De Funções De Referência

Leite

Marcone

Paiva

2018

HOLOS

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Uma alternativa para resolver problemas complexos de otimização é usando algoritmos meta-heurísticos. As meta-heurísticas são métodos aproximados que oferecem soluções aceitáveis para problemas de otimização. Nos últimos anos, algumas meta-heurísticas inspiradas no comportamento de animais da natureza, em especial aqueles que vivem em grupos, vêm sendo bastante utilizadas. Este trabalho tem como objetivo apresentar um breve estudo do desempenho de duas meta-heurísticas conhecidas como Algoritmo dos Vaga-lumes e Algoritmo dos Morcegos. A comparação é realizada por meio de vários experimentos computacionais para otimizar funções de referência clássicas da literatura. Para isso, foram realizadas 30 execuções independentes, considerando diferentes dimensões e quantidade de avaliações da função objetivo. Após os experimentos, alguns dados estatísticos foram apresentados e eles evidenciaram a superioridade do Algoritmo dos Vaga-lumes quando comparado com o Algoritmo dos Morcegos.

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Section: Aplicações Práticas Dos Algoritmos Do Vaga-lume E Do Morcegounclassified

Section: Introductionunclassified

Um Breve Estudo Sobre Os Algoritmos Dos Vaga-Lumes E Dos Morcegos Para Otimização De Funções De Referência

Leite

Marcone

Paiva

2018

HOLOS

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“…FFA works for nonlinear, multimodal, and complex systems and has the potential of coming out of local optima. FFA has become an increasingly important tool of swarm intelligence that has been applied in many areas of engineering optimization 26‐30 . FFA has been used in various field to solve problems such as job shop scheduling in manufacturing systems, 26 power dispatch problem in power system, 27 power loss in power system, 28 train operations, 29 and image compression 30 .…”

Section: Introductionmentioning

confidence: 99%

Optimal design of symmetric fractional delay filter using firefly algorithm

Srivastava

Dwivedi

Nagaria

2020

Circuit Theory & Apps

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Summary A fractional delay filter is used to increase the accuracy, preciseness, time synchronization, and stability of signal processing system. However, designing a fractional delay filter for a specified delay, without affecting spectral characteristics of the signal is challenging because of nondifferentiability and multimodal nature of its objective function. In this paper, a more accurate design technique has been proposed for designing fractional delay filters, based on a recently developed firefly algorithm and its improved version. The designed filters offer variable fractional delay. A novel symmetric structure of implementation has been used to design filters. The efficacy of the proposed technique is evaluated by considering a filter design example. The performance of the proposed technique is compared with the other exiting algorithm. The comparative analysis of finite impulse response (FIR) fractional delay filter design proves that the proposed algorithm has a smaller design error and an implementation complexity than the other reported existing algorithms. In addition to this, the designed FIR fractional delay filter is implemented on Xilinx Virtex‐7 for experimental validation.

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“…In comparison with traditional optimization techniques, meta-heuristic algorithms are more complex as they need many variables and parameters to be considered for a good accuracy. Firefly Algorithm (FA), developed by Yang in 2008 [14], is a meta-heuristic algorithm inspired from the adapted behavior of firefly swarms to develop optimizing function with multiple optima as an algorithm [15][16][17][18]. The FA is flexible in terms of implementation and problem formulation as compared to other algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimal sizing of distributed generation using firefly algorithm and loss sensitivity for voltage stability improvement

Hamid

Jipinus

Musirin

et al. 2020

IJEECS

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This paper proposes an optimization technique for distributed generation (DG) sizing in power system. The DG placement was done through Loss Sensitive (LS) technique to determine the suitable locations. The LS index is calculated such that the change in power losses is divided with generation increment and a rank of buses is obtained to identify the suitable locations for DG placement. Subsequently, a meta-heuristic algorithm, known as Firefly Algorithm (FA) was run to obtain the optimal size or capacity of the DG. The installation takes into consideration the aspect of voltage stability in terms of total real power losses and voltage profiles to be improved in the distribution system. Based on the experiment, the real power losses and voltage profiles were improved significantly as a result of the DG placement. In addition, the installation could prevent the power system from collapse as the reactive loading was increased to maximum.

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Firefly algorithm based solution to minimize the real power loss in a power system

Cited by 41 publications

References 24 publications

Um Breve Estudo Sobre Os Algoritmos Dos Vaga-Lumes E Dos Morcegos Para Otimização De Funções De Referência

Um Breve Estudo Sobre Os Algoritmos Dos Vaga-Lumes E Dos Morcegos Para Otimização De Funções De Referência

Optimal design of symmetric fractional delay filter using firefly algorithm

Optimal sizing of distributed generation using firefly algorithm and loss sensitivity for voltage stability improvement

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