Multi-verse optimization algorithm- and salp swarm optimization algorithm-based optimization of multilevel inverters

Ceylan, Oğuzhan

doi:10.1007/s00521-020-05062-8

Cited by 13 publications

(7 citation statements)

References 47 publications

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“…This paper improves on recent attempts to solve MLI optimization problems presented in [24] and [27], and more specifically,…”

Section: Introductionmentioning

confidence: 80%

“…Similar to the results of 7-level and 11level inverters, the mean best THDs and switching angles are explored by AGWO. The best design of the switching angles proposed by AGWO is θ [27] suggested a lower value of 4.31% for T H D = 0.8 compared to AGWO and mGWO. Moreover, we can see that the performance of PSO ,and MVO in this system can compete with GWO.…”

Section: Algorithm Comparison In 15-level MLImentioning

confidence: 98%

“…As for the numeri-Fig. 1 Single-phase, 7-level MLI from [27] cal method, Newton-Raphson has been used both for solving the selective harmonics equations (SHE) for MLIs [8] and for solving SHE of a relatively recent design of a flying capacitor MLI [9]. In [10], the authors combine artificial neural networks (ANN) with the Newton-Raphson method: The optimal switching angles are used to train the ANN, then the results are used as initial estimates for the NR-based optimization method.…”

Section: Introductionmentioning

confidence: 99%

“…The moth flame optimization (MFO) algorithm [23] was used in [24] to solve the problem of harmonic elimination of MLIs. Two recently developed heuristic algorithms, namely the multiverse optimization algorithm (MVO) [25] and the salp swarm optimization algorithm (SSA) [26], were also used in [27].…”

Section: Introductionmentioning

confidence: 99%

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Cascaded H-bridge multilevel inverters optimization using adaptive grey wolf optimizer with local search

2021

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With the transformation of transmission and distribution grids into smart grids that are more dominated by renewable energy, power electronics-based inverters that can improve power quality are becoming more visible. In order to maximize the output voltage quality and reduce the total harmonic distortion (THD), efficient operation of inverters is required. Therefore, in this paper, the problem of harmonic elimination in multilevel inverters is solved by using an adaptive grey wolf optimizer with local search. We have performed a grid search-based landscape analysis of the seven-level inverter to understand the behaviour of the proposed algorithm. For verification, the numerical results of the proposed adaptive grey wolf optimizer are compared with those of the original grey wolf optimization algorithm, a modified version of the grey wolf optimization algorithm, the particle swarm optimization algorithm, multi-verse optimization algorithm, and salp swarm algorithm. In the simulations, we solved the optimization model for three different structures of multilevel inverters (7, 11, and 15 levels) by changing the modulation indexes. It is found that the adaptive grey wolf optimization provides lower total harmonic distortion for different modulation indexes.

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“…This paper improves on recent attempts to solve MLI optimization problems presented in [24] and [27], and more specifically,…”

Section: Introductionmentioning

confidence: 80%

Section: Algorithm Comparison In 15-level MLImentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cascaded H-bridge multilevel inverters optimization using adaptive grey wolf optimizer with local search

2021

Self Cite

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“…The automobile routing issue of logistics dissemination can be described as: several dissemination automobiles are used to deliver goods from a dissemination center to several clients. The location and cargo request of each customer are certain, and the load volume of each dissemination automobile is certain [16,17]. It is required to reasonably arrange the automobile dissemination route, improve the objective task, and addresses the following assumptions: 1.…”

Section: Establish the Mathematical Design Of Logistics Dissemination...mentioning

confidence: 99%

Logistics Distribution Route Optimization Based on Improved Particle Swarm Optimization

Zhang¹,

Sharma²

2023

IJCAI

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This article improves the logistics distribution route and improves the distribution as well as transportation efficiency. The article combines the features of logistics dissemination along with mathematical designing of dissemination automobile routing issue. The mountain climbing procedure with strong local search ability is introduced into the particle swarm optimization (PSO) procedure to improve the offered approach. Two mountain climbing schemes are offered in this article, and two different hybrid (PSO) procedures are constructed. The experimental outcomes reveals the performance of Hybrid PSO scheme 1 and hybrid PSO scheme 2 offered in this paper which are better than that of standard PSO. Hybrid PSO scheme 2 offers best potential in efficiently solving the routing issue of logistics dissemination automobile. After the issue scale grows, the optimization advantages of Hybrid PSO scheme 2 are fully displayed. It was observed from the experimental analysis that using hybrid PSO scheme 2 to solve the logistics dissemination automobile routing issue can greatly shorten the dissemination mileage.Povzetek: Članek izboljšuje logistične distribucijske poti s hibridnim pristopom rojev delcev (PSO), kar znatno skrajša razdaljo distribucije in izboljša učinkovitost prevoza.

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An advanced Grey Wolf Optimization Algorithm and its application to planning problem in smart grids

et al. 2022

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Multi-verse optimization algorithm- and salp swarm optimization algorithm-based optimization of multilevel inverters

Cited by 13 publications

References 47 publications

Cascaded H-bridge multilevel inverters optimization using adaptive grey wolf optimizer with local search

Cascaded H-bridge multilevel inverters optimization using adaptive grey wolf optimizer with local search

Logistics Distribution Route Optimization Based on Improved Particle Swarm Optimization

An advanced Grey Wolf Optimization Algorithm and its application to planning problem in smart grids

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