Multi-Objective Artificial Bee Colony Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems

Yang, Nien-Che; Mehmood, Danish; Lai, Kai-You

doi:10.3390/math9243187

Cited by 6 publications

(6 citation statements)

References 49 publications

(63 reference statements)

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“…e least Manhattan distance strategy is used to choose the most equilibrium solution in the Pareto set among the obtained nondominated solutions. Additionally, Yang Nien-Che invents once more in the publication [29] by revalidating the Pareto solution set based on the artificial bee colony (ABC) method that has been enhanced by applying the artificial intelligence algorithm, which is more effective than the previous one. Khajouei Javad designed the most cost-effective and efficient way to deal with harmonics with passive filters for IEEE networks with nonlinear loads and Steinmetz circuits in the literature [30].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In literature [28] and literature [29], the author was working on a passive filter optimization algorithm, in which he compares the results of the algorithm proposed in the study with some classical algorithms (MOPSO, MOBA, SA) after processing. e GD results show the superiority of the proposed method by showing higher accuracy.…”

Section: Case Studymentioning

confidence: 99%

“…e top ranking is the optimal configuration with Current THD% of 0.823, COST of 0.902, and MBRP of 0.232. [34] 599.18 MOBSO [28] 587.28 MOABC [29] 586.69…”

Section: Case Studymentioning

confidence: 99%

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Passive Power Filter Optimization Problem Based on Adaptive Multipopulation NSGA-II and CRITIC-TOPSIS

Yuan

Liu

2022

Mathematical Problems in Engineering

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The best configuration of passive filters in extra-high voltage systems is investigated in this study using a two-stage multiobjective decision-making (MODM) framework. A collection of Pareto solutions is found using an adaptive multipopulation-modified nondominated ranking genetic algorithm (AMP NSGA-II) in the first stage. The goals taken into account include the least fundamental reactive power compensation losses, overall cost and maintenance cost, and simultaneous minimum harmonic current distortion rate. The objective weights are determined and the optimum solution is chosen in the second stage using the criteria importance interrelationship (CRITIC) and similarity ranking preference technique (TOPSIS). A number of examples show how the suggested method performs more effectively than the conventional and well-known algorithm and can identify the relationship between the objective functions, indicating that the suggested scheme has better superiority in filters and has a promising future in the solution of multiobjective problems.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

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Passive Power Filter Optimization Problem Based on Adaptive Multipopulation NSGA-II and CRITIC-TOPSIS

Yuan

Liu

2022

Mathematical Problems in Engineering

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“…The parameter design problem of the planar spiral inductor is a multiobjective optimization problem, which needs to consider the ratio of the internal and external diameter of the inductor, the inductor value, the quality factor Q, and the area constraints. The Artificial Bee Colony (ABC) algorithm has been applied to solve multi-objective optimization problems in the field of passive devices [6][7][8]. However, the ABC algorithm must balance the mining times of honey sources and the trade-off between exploitation and search capabilities.…”

Section: Introductionmentioning

confidence: 99%

Automatic Design of Planar Spiral Inductors Based on Improved Artificial Bee Colony Algorithm

Feng,

Guo,

Liu

2023

J. Phys.: Conf. Ser.

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Aiming at the low design efficiency of planar spiral inductors in Integrated Passive Devices (IPD), a design scheme for automatically searching the optimal parameters of planar spiral inductors is presented based on the Improved Artificial Bee Colony (IABC) algorithm. By improving the single π model, the universality of the inductor equivalent model is improved, and the extracted model is convenient for the parameter optimization of the inductor. The artificial bee colony (ABC) algorithm is improved by introducing multi-neighborhood topology (MNT) and modification rate mechanism, which greatly improves the optimization efficiency of the original algorithm. The optimization parameters of the improved algorithm are simulated in ADS, and the results are consistent with the multiple design cases of planar spiral inductors, which verifies the effectiveness of the algorithm. The improved algorithm significantly improves the design efficiency of the planar spiral inductor, making the design time of a single inductor only in seconds, and the accuracy rate is more than 90%.

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“…Recently, researchers from both academia and industry have conducted in-depth analyses of the causes, effects, suppression methods, and related technologies of harmonics [4][5][6][7][8]. It is widely agreed that the optimal solution to harmonics is to install power filters at the source of harmonic generation and at the nearest end of the harmonic source.…”

Section: Introductionmentioning

confidence: 99%

Cloud Server-Assisted Remote Monitoring and Core Device Fault Identification for Dynamically Tuned Passive Power Filters

Wang,

Chen,

Deng

2023

Applied Sciences

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Reliability and safety are crucial for the operation of a dynamically tuned passive power filter (DTPPF). Safe performance of DTTPFs implies complete normal filtering without failure within a specified period. To prevent potential disaster or economic loss, it is desirable to achieve early warning of any core device faults in a DTPPF based on its running state and to optimize its harmonic mitigation performance. In this paper, we explore effective methods for identifying core device faults in DTPPFs. First, we summarize the characteristic parameters of faults, running state parameters, parameters required for fault monitoring, and fault type parameters. Then, a cloud server-assisted remote monitoring and fault identification system for DTPPF is proposed, which consists of monitoring system’s architecture and cloud servers’ software architecture as well as software design of the back-end service layer and functional design of the front-end application layer. Our experiments demonstrate that the proposed system can monitor the real-time operational status of the DTPPF, enabling remote diagnosis and identification of core device faults. Moreover, it is user-friendly, as it is capable of optimizing equipment maintenance schedules and utilizing manufacturers’ service capacities. Therefore, this research provides a theoretical foundation for harmonic mitigation in low-voltage distribution networks and is valuable for practical engineering applications in industrial power grids.

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Multi-Objective Artificial Bee Colony Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems

Cited by 6 publications

References 49 publications

Passive Power Filter Optimization Problem Based on Adaptive Multipopulation NSGA-II and CRITIC-TOPSIS

Passive Power Filter Optimization Problem Based on Adaptive Multipopulation NSGA-II and CRITIC-TOPSIS

Automatic Design of Planar Spiral Inductors Based on Improved Artificial Bee Colony Algorithm

Cloud Server-Assisted Remote Monitoring and Core Device Fault Identification for Dynamically Tuned Passive Power Filters

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