Enhanced Sine–Cosine Algorithm for Optimal Planning of Distribution Network by Incorporating Network Reconfiguration and Distributed Generation

Raut, Usharani; Mishra, Sivkumar

doi:10.1007/s13369-020-04808-9

Cited by 26 publications

(18 citation statements)

References 53 publications

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“…As shown in (3) is ensured by adjusting the boundaries of new solutions. Meanwhile if (4) and ( 5) are not maintained, then a high value will be assigned to the fitness value, otherwise, the fitness value is determined as (13).…”

Section: The Modified Sfo For Nr-dgp Problemmentioning

confidence: 99%

“…Step 5: Update the current sunflower plant population The new solutions are adjusted if they are out of bounds. Then, they are adapted by (12) for mapping with the NR-DGP and evaluated the quality by using (13). Then, the current sunflower plants are updated if new solutions have the better quality than that of the current ones.…”

Section: The Modified Sfo For Nr-dgp Problemmentioning

confidence: 99%

“…In addition, in [10] another improved version of BPSO called Chaotic BPSO has been also applied to the NR problem for power loss reduction. In addition, some of recent algorithms have been successful proposed for the NR-DGP problem such as water cycle algorithm [11], firefly algorithm (FA), gravitational search algorithm (GSA) [12], sine cosine algorithm (SCA) [13], moth flame optimization [14], salp swarm algorithm [15], and threedimensional group search algorithm (3DGSO) [16].…”

Section: Introductionmentioning

confidence: 99%

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Modified sunflower optimization for network reconfiguration and distributed generation placement

Nguyen

Duong

et al. 2022

IJECE

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<span lang="EN-US">This paper proposed modified sunflower optimization (MSFO) for the combination of network reconfiguration and distributed generation placement problem (NR-DGP) to minimize power loss of the electric distribution system (EDS). Sunflower optimization (SFO) is inspired form the ideal of sunflower plant motion to get the sunlight and its reproduction. To enhance the performance of SFO, it is modified to MSFO wherein, the pollination and mortality techniques have been modified by using Levy distribution and mutation of the best solutions. The results are evaluated on two test systems. The efficiency of MSFO is compared with that of the original SFO and other algorithms in literature. The comparisons show that MSFO outperforms to SFO and other methods in obtained optimal solution. Furthermore, MSFO demonstrates the better statistical results than SFO. So, MSFO can be a powerful approach for the NR-DGP problem.</span>

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Section: The Modified Sfo For Nr-dgp Problemmentioning

confidence: 99%

Section: The Modified Sfo For Nr-dgp Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modified sunflower optimization for network reconfiguration and distributed generation placement

Nguyen

Duong

et al. 2022

IJECE

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“…( 2019 ) Radial Distribution Networks Ismael et al. ( 2017 ), Ang and Leeton ( 2019 ) Abdelsalam ( 2020 ), Raut and Mishra ( 2019 ) Raut and Mishra ( 2021 ) Optimal Load Frequency Control Mishra et al. ( 2018 ) , Babaei and Safari ( 2020 ) Optimal PMU Placement Laouamer et al.…”

Section: Applications Of the Sine Cosine Algorithmmentioning

confidence: 99%

A comprehensive survey of sine cosine algorithm: variants and applications

et al. 2021

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Sine Cosine Algorithm (SCA) is a recent meta-heuristic algorithm inspired by the proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in 2016, SCA has attracted great attention from researchers and has been widely used to solve different optimization problems in several fields. This attention is due to its reasonable execution time, good convergence acceleration rate, and high efficiency compared to several well-regarded optimization algorithms available in the literature. This paper presents a brief overview of the basic SCA and its variants divided into modified, multi-objective, and hybridized versions. Furthermore, the applications of SCA in several domains such as classification, image processing, robot path planning, scheduling, radial distribution networks, and other engineering problems are described. Finally, the paper recommended some potential future research directions for SCA.

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“…This is the power balance constraint, which states that power output from the grid and DG must be equal to power demand by the consumers and power losses in the lines [30,31]. This constraint can be expressed as Equation 9.…”

Section: 41equality Constraintsmentioning

confidence: 99%

Minimization of losses in a distribution system with network reconfiguration, distributed generation and D-STATCOM

Salkuti¹

2021

IJATEE

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Enhanced Sine–Cosine Algorithm for Optimal Planning of Distribution Network by Incorporating Network Reconfiguration and Distributed Generation

Cited by 26 publications

References 53 publications

Modified sunflower optimization for network reconfiguration and distributed generation placement

Modified sunflower optimization for network reconfiguration and distributed generation placement

A comprehensive survey of sine cosine algorithm: variants and applications

Minimization of losses in a distribution system with network reconfiguration, distributed generation and D-STATCOM

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