A new fuzzy optimal allocation of detuned passive filters based on a Nonhomogeneous Cuckoo Search Algorithm considering resonance constraint

Ayoubi, Masoud; Hooshmand, Rahmat‐Allah

doi:10.1016/j.isatra.2018.12.034

Cited by 13 publications

(10 citation statements)

References 17 publications

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“…In the case of B-n31-k5, the customers who order goods weighing in the range of [19,25] belong to large customers. e customers who order goods weighing in the range of [9,18] belong to small and medium customers. e customers who order goods weighing in the range of [2,8] belong to small and retail customers.…”

Section: Vrpsc Experiments With Distinguishing Customermentioning

confidence: 99%

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Adaptive Cultural Algorithm-Based Cuckoo Search for Time-Dependent Vehicle Routing Problem with Stochastic Customers Using Adaptive Fractional Kalman Speed Prediction

Han

2020

Mathematical Problems in Engineering

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For the Time-Dependent Vehicle Routing Problem with Stochastic Customers (TDVRPSC), an adaptive Cultural Algorithm-Based Cuckoo Search (CACS) has been proposed in this paper. The convergence of the new algorithm is proved. An adaptive fractional Kalman filter (AFKF) for traffic speed prediction is proposed. An adaptive mechanism for choosing the covariance of state noise is designed. Its mathematical process is proved. Several benchmark instances with different scales are tested, and new solutions are discovered, which are better than the published solutions. The effects of the parameters on the convergence and the results are studied. According to cargo weight of customers to be delivered, the customers can be divided into large, small, and retail customers. The algorithm is tested with fixed demand probability and also different customer types with stochastic demand. The traffic speeds in different business districts in Xiamen at different times are predicted by AFKF. The results show that AFKF has smaller prediction error and better prediction accuracy than fractional Kalman filter and Kalman filter. The effect of different fractional orders on prediction error is compared. The performance of the new algorithm is compared with that of the cultural algorithm and the Cuckoo Search. The result shows that the new algorithm can efficiently and effectively solve DTVRPSC and improve the accuracy of vehicle routing planning of time-varying actual urban traffic road.

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Section: Vrpsc Experiments With Distinguishing Customermentioning

confidence: 99%

“…Ishak Boushaki et al proposed a quantum chaotic Cuckoo Search algorithm for data clustering [17]. Ayoubi et al proposed a nonhomogeneous Cuckoo Search algorithm for allocation of passive filters [18].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Cultural Algorithm-Based Cuckoo Search for Time-Dependent Vehicle Routing Problem with Stochastic Customers Using Adaptive Fractional Kalman Speed Prediction

Han

2020

Mathematical Problems in Engineering

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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%

“…[ 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. The PPF installation cost and THD at PCC have been selected as the OF considering the uncertainty of NL harmonic currents.…”

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 [10], the frequency indices are considered as constraint to avoid resonance for all buses. The purpose of this work is only the minimisation of the filter cost.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of passive filters considering the effect of Steinmetz circuit resonance under unbalanced and non‐sinusoidal conditions

Khajouei

Esmaeili

Nosratabadi

2020

IET Generation, Transmission & Distribution

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A new fuzzy optimal allocation of detuned passive filters based on a Nonhomogeneous Cuckoo Search Algorithm considering resonance constraint

Cited by 13 publications

References 17 publications

Adaptive Cultural Algorithm-Based Cuckoo Search for Time-Dependent Vehicle Routing Problem with Stochastic Customers Using Adaptive Fractional Kalman Speed Prediction

Adaptive Cultural Algorithm-Based Cuckoo Search for Time-Dependent Vehicle Routing Problem with Stochastic Customers Using Adaptive Fractional Kalman Speed Prediction

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

Optimal design of passive filters considering the effect of Steinmetz circuit resonance under unbalanced and non‐sinusoidal conditions

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