Cuckoo search algorithm for power loss minimization by optimal capacitor allocation in radial power systems

Baysal, Yesim A.; Altaş, İsmail H.

doi:10.1109/inista.2016.7571822

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…Gnanasekaran et al (2016) proposes shark smell optimization technique for the optimal allocation of the capacitors in radial distribution feeder, the technique is verified by testing it on 118 bus system which showed its improved results regarding total power loss and total cost compared to some other methods, however the total installed KVAr of the capacitors is much higher compared to some other methods such as artificial bee colony (ABC) used in El-Fergany et al (2014). Devabalaji et al, 2016) the authors used hybrid method in which the voltage stability index determines the best locations for the installed capacitors and the sizes of capacitors are determined using cuckoo search algorithm, Unlike Baysal et al (2016) where the cuckoo search was used to determine the optimal location and sizes of capacitors installed on radial distribution feeder, the method is implemented on 34 bus test feeder. The net saving seems to be promising compared to other techniques but the total kVAR of the installed capacitors is much higher than other previously implemented methods as particle swarm optimization (PSO) and plant growth simulation algorithm (PGS) (Prakash et al, 2007;Rao et al, 2011), while the minimum bus voltage in per unit.…”

Section: Introductionmentioning

confidence: 98%

“…Its worth mentioning that the previously mentioned algorithms could be modified or used with other techniques as loss sensitivity factors or other optimization techniques as hybrid methods in the process of optimal location and sizing of capacitors in radial distribution feeders. Baysal et al (2016) uses the traditional cuckoo search algorithm to minimize the power losses in the system and maximize annual net saving. To validate the method, it is applied to a 9 bus feeder system to show the technique merits.…”

Section: Introductionmentioning

confidence: 99%

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Solution of the capacitor allocation problem using an improved whale optimization algorithm

Shehata¹,

Mekhamer²,

Abdelaziz³

et al. 2018

Int. J. Eng. Sci. Tech

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A superior optimization technique called whale optimization algorithm introduced in 2016 which belongs to swarm intelligence family is used and implemented in this paper with some improvements to solve the problem of capacitor allocation in radial distribution feeders. In order to show the effectiveness of the proposed technique, three test distribution feeders are used (15 bus, 34 bus and 69 bus test systems). The obtained results are compared with other optimization techniques prove that the proposed method gives the optimal results; most reduction in system power losses, voltage profile enhancement and lower annual cost among the other techniques applied to the same distribution feeders.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Solution of the capacitor allocation problem using an improved whale optimization algorithm

Shehata¹,

Mekhamer²,

Abdelaziz³

et al. 2018

Int. J. Eng. Sci. Tech

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“…Este método foi utilizado para alocação de capacitores buscando minimizar perdas com menor custo de investimento em um determinado horizonte de planejamento. Em Baysal & Altas (2016), foi utilizado o Cukoo Search Algorithm (CSA), algoritmo inspirado no parasitismo de algumas espécies do pássaro cuco, que colocam seus ovos em ninhos de outras espécies de aves hospedeiras. Neste trabalho a técnica de otimização foi utilizada para redução de perdas e melhorias nos perfis de tensão.…”

Section: Introductionunclassified

Metodologia para alocação ótima de capacitores em sistemas de distribuição considerando restrições de tensão, mitigação do desequilíbrio e minimização de perdas

Batista

BARBOSA

Araujo

et al. 2021

Procedings Do XV Simpósio Brasileiro De Automação Inteligente

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This paper presents a two-step methodology for optimal capacitor placement in unbalanced power distribution systems considering voltage constraints, imbalance mitigation and reduction of technical losses using a genetic algorithm technique. In the optimization process, both in the first and second stage, the uncertainties arising from the loading levels of the feeders and the demand for loads in the nodes are considered, seeking to better represent the operation of the real systems, thus allowing a better assessment of the ideal nodes for capacitors placement. In order to validate the proposed methodology, it was used the IEEE 13 and IEEE 37 Nodes Test Feeders.Resumo: Este artigo apresenta uma metodologia em duas etapas para alocação ótima de capacitores em sistemas de distribuição de energia desequilibrados considerando restrições de tensão, mitigação de desequilíbrio e redução de perdas técnicas utilizando a técnica de algoritmos genéticos. No processo de otimização, tanto na primeira quanto na segunda etapa, são consideradas as incertezas provenientes dos níveis de carregamento dos alimentadores e da demanda das cargas nos nós buscando representar de maneira mais adequada a operação dos sistemas reais, permitindo assim uma melhor avaliação das barras ideais para alocação dos capacitores. Para validar a metodologia proposta, foram utilizados os alimentadores IEEE 13 e IEEE 37 barras.

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“…It is worth the mention that other techniques are used to solve the OPF, such as Cuckoo Search Algorithm (CSA) [23][24][25] and firefly optimization algorithm [26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Modified Flower Pollination Algorithm Constrained Optimal Power Flow

Hocine¹,

Salem²

2019

ISI

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In power systems, the power flow must satisfy a set of operational and safety requirements. It is a highly nonlinear problem to optimize the power flow. In this paper, the flower pollination algorithm (FPA) is modified and applied to optimize the power flow. Firstly, the author set up a mathematical model for power flow optimization problem, and formulated all the constraints. Next, the FPA was introduced in details, including the self-pollination, cross-pollination and other operations. After that, the local search strategy of the FPA was modified to replace the worst individuals in the current population with the best individuals in the previous population. Finally, the modified FPA (MFPA) was proved more efficient and better in convergence than standard algorithms like the firefly algorithm.

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Cuckoo search algorithm for power loss minimization by optimal capacitor allocation in radial power systems

Cited by 8 publications

References 10 publications

Solution of the capacitor allocation problem using an improved whale optimization algorithm

Solution of the capacitor allocation problem using an improved whale optimization algorithm

Metodologia para alocação ótima de capacitores em sistemas de distribuição considerando restrições de tensão, mitigação do desequilíbrio e minimização de perdas

Modified Flower Pollination Algorithm Constrained Optimal Power Flow

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