Integrated feasible direction method and genetic algorithm for optimal planning of harmonic filters with uncertainty conditions

Chang, Ying-Pin; Low, Chinyao; Hung, Shih-Yu

doi:10.1016/j.eswa.2008.02.033

Cited by 15 publications

(10 citation statements)

References 12 publications

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“…Thus, our objective is to find a gain K which keeps both and at a low level. Other system parameters are given as follow: (19) where DPF represents the compensated load-displacement power factor, ad '1' means the fundamental component.…”

Section: ⅱ Problem Formulation a Two Popular Topologies Of Hapfmentioning

confidence: 99%

“…Some scholars use these meta-heuristic methods to designed the filters in the power system. For example, predator-prey based firefly optimization [15], ant colony optimization [16], particle swarm optimization [17], ant direction hybrid DE [18], genetic algorithms [19], bacterial foraging optimization [20], etc. However, most of these methods are applied to design PPF; a small number of meta-heuristic methods are used to design HAPF.…”

Section: ⅰ Introductionmentioning

confidence: 99%

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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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Section: ⅱ Problem Formulation a Two Popular Topologies Of Hapfmentioning

confidence: 99%

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

View full text Add to dashboard Cite

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“…To illustrate previous research works which have been conducted regarding the methodology and different types of the filters used in the harmonic compensation framework, Table 1 comprehensively shows the harmonic compensation taxonomy including various studies. [ 7–52 ] Based on the magnitude of the harmonic pollution by NLs, it was decided to utilize one or multiple PPFs and APLCs to participate in harmonic compensation. This framework can consist of an objective function (OF) or multiOFs, uncertainty consideration, single‐objective or multiobjective solution method, etc.…”

Section: Introductionmentioning

confidence: 99%

“…The utilization of PPFs has been presented in various studies. [ 7–31 ] As shown in Table 1, the single‐objective metaheuristic algorithms, such as hybrid differential algorithm, [ 7 ] particle swarm optimization (PSO), [ 8 ] genetic algorithm (GA), [ 9,11 ] ant colony, [ 10 ] bacterial foraging optimization, [ 12 ] whale optimization, [ 13 ] cuckoo search algorithm, [ 16 ] adaptive dynamic clone selection algorithm, [ 20 ] and modified bat algorithm, [ 21 ] are utilized for solving the harmonic compensation problem considering PPFs. For instance, a new fuzzy method in the study by Ayoubi et al [ 16 ] has been used for fixed and switched PPF allocation, solving by the nonhomogeneous cuckoo search algorithm and considering preventing resonance conditions as a vital constraint.…”

Section: Introductionmentioning

confidence: 99%

A New Optimization Framework for Harmonic Compensation Considering Plug‐in Electric Vehicle Penetration Using Adaptive Particularly Tunable Fuzzy Chaotic Particle Swarm Optimization

2021

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Plug‐in electric vehicles (PEVs) can contribute to eliminating undesirable harmonics generated by nonlinear loads. In this study, a novel stochastic optimization approach for harmonic compensation is proposed which is capable of optimizing contrary objectives, including total harmonic distortion and harmonic inject current, simultaneously, while meeting the relevant constraints. This problem can be influenced by the uncertainty of PEVs which is reflected in the force outage rate concept. The Monte–Carlo simulation technique is implemented to consider the uncertainty associated with PEVs by generating plausible scenarios with the aim of converting the mentioned framework to the respective deterministic equivalents. Afterward, adaptive particularly tunable fuzzy chaotic particle swarm optimization (APTFCPSO) is utilized, based on the weighted sum method, and the acquired results are compared with those obtained by other implemented swarm intelligence‐based algorithms. Accordingly, at first, several benchmark optimization functions are considered to verify the performance of the APTFCPSO. Afterward, active power line conditioners (APLCs) and PEVs are separately employed for harmonics cancellation in the deterministic form. After adopting the scenario reduction technique, the optimization framework is solved for each remaining scenario by the mentioned procedure. The statistical analysis reveals that PEVs outperform APLCs to cancel harmonic orders defined in a 14‐node micro‐grid.

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“…In [8], an enhanced current control approach is proposed that seamlessly integrates system harmonic mitigation capabilities with the primary DG power generation function. In [9], a genetic algorithm and a feasible direction method are applied for optimal planning of harmonic filters with uncertainty conditions. An optimal method for active power filter is presented in [10] to improve power quality.…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Active Power Filter On real distribution network for improvement of power quality by use of BBO: A case study

Samadaei

Khosravi

Sheikholeslami

2017

IIUMEJ

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ABSTRACT:Â According to development of power electronics device, harmonic distortion spread on the network. Thus harmonic is a threat for instrument, network, decreasing of line capacity and etc. Active power ï¬lter (APF) can be employed for harmonic compensation in power systems. In this paper a distorted distribution feeder is considered and analyzed from power quality viewpoint using power analyzer device and simulated in MATLAB-Mfile. Then the size and place of active power filters are determined by use of Biogeography Based Optimization (BBO). The goal of this optimization is minimizing of losses and total harmonic distortion (THD) in feeder by considering economical cost.Â The performance of the approaches are assessed and appreciated by a case study on the Ghaemshahr-Iran Distribution network. Measurement is done on the city network by power analyzer CA8310. All data was collected on Computer. Then researcher algorithm BBO, it is selected the best place and size for Active power filter. The results show a good performance.

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Integrated feasible direction method and genetic algorithm for optimal planning of harmonic filters with uncertainty conditions

Cited by 15 publications

References 12 publications

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

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

A New Optimization Framework for Harmonic Compensation Considering Plug‐in Electric Vehicle Penetration Using Adaptive Particularly Tunable Fuzzy Chaotic Particle Swarm Optimization

Optimal Allocation of Active Power Filter On real distribution network for improvement of power quality by use of BBO: A case study

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