Multi‐objective optimal design of passive power filter for aircraft starter/generator system application

Zhao, Dan; Liu, Weiguo; Shen, Ke; Zhao, Guodong; Wang, Xin

doi:10.1049/joe.2018.0046

Cited by 7 publications

(5 citation statements)

References 16 publications

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“…Several studies have calculated the parameters of PPFs and evaluated the sizing, sitting, type, and number of PPFs [13,20], minimizing the initial investment costs [19], minimizing the harmonic distortion [18], and maximizing the reactive power compensation [21]. In [13], power loss and investment costs were used to evaluate the PPF design and limitations, including the number of PPFs, limited buses for installation of PPFs, and total harmonic distortion in all buses.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In recent years, heuristic optimization algorithms have been used in PPF design for their effective and optimal results. A genetic algorithm (GA) [24,25], particle swarm optimization (PSO) [18], and simulated annealing (SA) [26] were used for PPF designs. In [18], the PSO method was used to optimize the design of PPFs for aircraft starter/generator system applications.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A genetic algorithm (GA) [24,25], particle swarm optimization (PSO) [18], and simulated annealing (SA) [26] were used for PPF designs. In [18], the PSO method was used to optimize the design of PPFs for aircraft starter/generator system applications. The main objective was to reduce the weight and volume of the filter, instead of mitigating harmonics.…”

Section: Literature Reviewmentioning

confidence: 99%

“…PPFs are the most effective and commonly used because they are simple and economical [12]. Several studies have shown the effectiveness of PPFs in reducing harmonics from nonlinear systems [13][14][15][16][17][18][19].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

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

Yang

Mehmood

2022

Mathematics

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Harmonic distortion in power systems is a significant problem, and it is thus necessary to mitigate critical harmonics. This study proposes an optimal method for designing passive power filters (PPFs) to suppress these harmonics. The design of a PPF involves multi-objective optimization. A multi-objective bee swarm optimization (MOBSO) with Pareto optimality is implemented, and an external archive is used to store the non-dominated solutions obtained. The minimum Manhattan distance strategy was used to select the most balanced solution in the Pareto solution set. A series of case studies are presented to demonstrate the efficiency and superiority of the proposed method. Therefore, the proposed method has a very promising future not only in filter design but also in solving other multi-objective optimization problems.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introduction 1backgroundmentioning

confidence: 99%

See 2 more Smart Citations

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

Yang

Mehmood

2022

Mathematics

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“…It is a combination of capacitive and inductive pairs, and the different sizes of capacitors and inductors result in different frequency response characteristics of PPF. Thus, it is simple to use with a relatively low economical cost, which enables PPF to become the most commonly used technology for harmonic suppression [4], [5], [6]. However, the static frequency response of PPF cannot catch up with the dynamic changes of nonlinear loads.…”

Section: ⅰ Introductionmentioning

confidence: 99%

An Adaptive Sine-Cosine Moth-Flame Optimization Algorithm for Parameter Identification of Hybrid Active Power Filters in Power Systems

Chen

et al. 2020

IEEE Access

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Hybrid active power filter (HAPF) is a novel technique of harmonic filter which combines superiorities of both active and passive filters. However, extracting appropriate parameters of the HAPF, including active filter gain, passive inductive, and capacitive reactance within a constraint space is still a challenging task. To obtain more accurate parameters of HAPF, this paper proposed a new population-based algorithm named ASC-MFO. In ASC-MFO, the swarm is divided into two sub-swarms, i.e., exploitation group and the exploration group. The exploitation group adopts the SFM in the MFO algorithm to enhance the exploitation ability, while the exploration group utilizes the SCM in the SCA algorithm to emphasize exploration. Besides, a personal best flame generation (PFG) strategy and a hybrid exemplar generation (HEG) strategy are developed for the exploitation group and the exploration group to further enhance the exploitation ability and the exploration ability of the two subgroups, respectively. Moreover, an adaptive strategy is proposed to automatically resize the population number of two sub-swarms during the iterative process, which can precisely balance the exploration and exploitation ability between groups in every single generation. The proposed ASC-MFO is applied to design the two most commonly used topologies of the HAPF, where each topology contains four actual cases. Comprehensive experimental results demonstrate that ASC-MFO obtains an excellent performance among those well-established algorithms, especially in the aspect of accuracy and reliability. INDEX TERMS Sine cosine algorithm (SCA), Moth flame optimization (MFO), Swarm Global optimization, Hybrid active power filter (HAPF).

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Virtual-Impedance-Based Decoupling Control

Liu

2023

Synthesis Lectures on Power Electronics

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Multi‐objective optimal design of passive power filter for aircraft starter/generator system application

Cited by 7 publications

References 16 publications

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

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

An Adaptive Sine-Cosine Moth-Flame Optimization Algorithm for Parameter Identification of Hybrid Active Power Filters in Power Systems

Virtual-Impedance-Based Decoupling Control

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