Morteza Ghaseminezhad, Aref Doroudi, Seyed Hossein Hosseinian and Alireza Jalilian
Voltage fluctuation (flicker) is a power quality disturbance that can produce several undesirable effects on industrial equipment. This paper aims to present the methodology and…
Abstract
Purpose
Voltage fluctuation (flicker) is a power quality disturbance that can produce several undesirable effects on industrial equipment. This paper aims to present the methodology and results of investigations undertaken to examine the speed and torque of an induction motor (IM) under voltage fluctuation conditions.
Design/methodology/approach
The IM response to different characteristics of voltage fluctuations is presented. It will be shown that under a special condition the IM torque can even reach two times the rated torque. To show how this occurs, a qualitative discussion is given on the motor response by linearized equations.
Findings
The small-signal analysis was used to determine the frequency which leads to maximum speed fluctuations. It was shown that, if the motor is excited with a modulation frequency (resonant frequency) which is one of its natural frequencies (modes), the mode will act as a fluctuating amplifier and greatly increase the amplitude of torque and speed fluctuations. Sensitivity analysis is also carried out to evaluate the influence of motor parameters on the resonance frequency. The results show that the resonance frequency is not affected at all by the changes in magnetizing reactance. This has been shown that magnetic saturation does not have any impact on the resonance frequency. The most effective parameters are rotor and stator resistances.
Originality/value
With the increasing popularity and use of arc furnace loads in the metallurgy industry and due to the wide application of large IMs in the industry, it is possible that the frequency of torque pulsation locates near a natural frequency and then will create an oscillation with a large magnitude, potentially leading to accelerated fatigue or severe damage of shaft. However, if this phenomenon occurs in industries, the resonance frequency must be filtered from the input voltage. Experimental results on a 1.1 kW, 380 V, 50 Hz, 2 pole IM are used to validate the accuracy of simulation results.
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B. Vahidi, B. Hemmatian and S.H. Hosseinian
To find an easy and accurate method for evaluating the Pollaczek's integral in earth‐return path impedance calculation.
Abstract
Purpose
To find an easy and accurate method for evaluating the Pollaczek's integral in earth‐return path impedance calculation.
Design/methodology/approach
The Monte Carlo method of evaluating the Pollaczek's integral is introduced.
Findings
The Monte Carlo method is easy and accurate method for this computation.
Research limitations/implications
Using proposed method in cases of earth stratification.
Practical implications
The proposed method can be used in power system transient software.
Originality/value
The proposed method introduces a computation method for calculation of Pollaczek's integral which is valuable for power engineers.
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Ramezan Ali Naghizadeh, Behrooz Vahidi and Seyed Hossein Hosseinian
The purpose of this paper is to propose an accurate model for simulation of inrush current in power transformers with taking into account the magnetic core structure and…
Abstract
Purpose
The purpose of this paper is to propose an accurate model for simulation of inrush current in power transformers with taking into account the magnetic core structure and hysteresis phenomenon. Determination of the required model parameters and generalization of the obtained parameters to be used in different conditions with acceptable accuracy is the secondary purpose of this work.
Design/methodology/approach
The duality transformation is used to construct the transformer model based on its topology. The inverse Jiles-Atherton hysteresis model is used to represent the magnetic core behavior. Measured inrush waveforms of a laboratory test power transformer are used to calculate a fitness function which is defined by comparing the measured and simulated currents. This fitness function is minimized by particle swarm optimization algorithm which calculates the optimal model parameters.
Findings
An analytical and simple approach is proposed to generalize the obtained parameters from one inrush current measurement for simulation of this phenomenon in different situations. The measurement results verify the accuracy of the proposed method. The developed model with the determined parameters can be used for accurate simulation of inrush current transient in power transformers.
Originality/value
A general and flexible topology-based model is developed in PSCAD/EMTDC software to represent the transformer behavior in inrush situation. The hysteresis model parameters which are obtained from one inrush current waveform are generalized using the structure parameters, switching angle, and residual flux for accurate simulation of this phenomenon in different conditions.
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Brijesh Upadhaya, Paavo Rasilo, Lauri Perkkiö, Paul Handgruber, Anouar Belahcen and Antero Arkkio
Improperly fitted parameters for the Jiles–Atherton (JA) hysteresis model can lead to non-physical hysteresis loops when ferromagnetic materials are simulated. This can be…
Abstract
Purpose
Improperly fitted parameters for the Jiles–Atherton (JA) hysteresis model can lead to non-physical hysteresis loops when ferromagnetic materials are simulated. This can be remedied by including a proper physical constraint in the parameter-fitting optimization algorithm. This paper aims to implement the constraint in the meta-heuristic simulated annealing (SA) optimization and Nelder–Mead simplex (NMS) algorithms to find JA model parameters that yield a physical hysteresis loop. The quasi-static B(H)-characteristics of a non-oriented (NO) silicon steel sheet are simulated, using existing measurements from a single sheet tester. Hysteresis loops received from the JA model under modified logistic function and piecewise cubic spline fitted to the average M(H) curve are compared against the measured minor and major hysteresis loops.
Design/methodology/approach
A physical constraint takes into account the anhysteretic susceptibility at the origin. This helps in the optimization decision-making, whether to accept or reject randomly generated parameters at a given iteration step. A combination of global and local heuristic optimization methods is used to determine the parameters of the JA hysteresis model. First, the SA method is applied and after that the NMS method is used in the process.
Findings
The implementation of a physical constraint improves the robustness of the parameter fitting and leads to more physical hysteresis loops. Modeling the anhysteretic magnetization by a spline fitted to the average of a measured major hysteresis loop provides a significantly better fit with the data than using analytical functions for the purpose. The results show that a modified logistic function can be considered a suitable anhysteretic (analytical) function for the NO silicon steel used in this paper. At high magnitude excitations, the average M(H) curve yields the proper fitting with the measured hysteresis loop. However, the parameters valid for the major hysteresis loop do not produce proper fitting for minor hysteresis loops.
Originality/value
The physical constraint is added in the SA and NMS optimization algorithms. The optimization algorithms are taken from the GNU Scientific Library, which is available from the GNU project. The methods described in this paper can be applied to estimate the physical parameters of the JA hysteresis model, particularly for the unidirectional alternating B(H) characteristics of NO silicon steel.
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Omid Abdi Monfared, Aref Doroudi and Amin Darvishi
Squirrel cage induction motors suffer from several faults such as rotor broken bar. One of the powerful methods to detect induction motor faults is the line current signature…
Abstract
Purpose
Squirrel cage induction motors suffer from several faults such as rotor broken bar. One of the powerful methods to detect induction motor faults is the line current signature analysis. This paper aims to present a novel algorithm based on continuous wavelet transform (CWT) to diagnose a rotor broken bar fault.
Design/methodology/approach
The proposed CWT has high flexibility in monitoring any frequency of interest in a waveform. Based on this transform, stator current frequency spectrum is analyzed to diagnose the rotor broken bar fault. The algorithm distinguishes the healthy motor from the faulted one based on a proper index. The method can be used in steady-state running time of induction motor and under different loading conditions. Experimental results are presented to show the validity of the proposed approach.
Findings
The proposed index considerably increases at the broken bars conditions compared to the healthy conditions. It can clearly diagnose the faulty conditions. The experimental results are found to be in good agreement with the theoretical and simulated results. The proposed method can reduce the noise and spectral leakage effects.
Originality/value
The main contribution of the paper are as follows: using CWT for detection of broken bar faults; introducing a proper index for diagnosing broken bars; and introducing a supplementary index to reduce the noise and spectral leakage effects.
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Zibo Li, Zhengxiang Yan, Shicheng Li, Guangmin Sun, Xin Wang, Dequn Zhao, Yu Li and Xiucheng Liu
The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.
Abstract
Purpose
The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.
Design/methodology/approach
In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance the capacity of polynomials approximation and the manifolds optimization method was introduced to solve the co-related optimization problem.
Findings
Two multi-variable Laguerre polynomials regression methods are designed. Firstly, Laguerre polynomials are combined with feature selection method. Secondly, manifolds component analysis is adopted in cascaded Laguerre polynomials regression method. Two methods are brought to enhance the accuracy of multi-variable regression method.
Research limitations/implications
With the increasing number of variables in regression problem, the stable accuracy performance might not be kept by using manifold-based optimization method. Moreover, the methods mentioned in this paper are not suitable for the classification problem.
Originality/value
Experiments are conducted on three types of datasets to evaluate the performance of the proposed regression methods. The best accuracy was achieved by the combination of cascade, manifold optimization and Chebyshev polynomials, which implies that the manifolds optimization has stronger contribution than the genetic algorithm and Laguerre polynomials.
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Mohammad Esmaeil Nazari and Mahsa Zarrini Farahmand
The purpose of this study is to solve the optimal operation strategy problem of plug-in electric vehicles (PEV) parking as a demand response (DR) program and hydro storage as an…
Abstract
Purpose
The purpose of this study is to solve the optimal operation strategy problem of plug-in electric vehicles (PEV) parking as a demand response (DR) program and hydro storage as an energy storage system in a smart grid environment using a heuristic algorithm.
Design/methodology/approach
Studying the smart grid with DR, renewable energy resources and energy storage systems is necessary. To do this, the heuristic optimization algorithm is developed to solve the scheduling problem. This deterministic algorithm benefits from the definition of appropriate fitness functions.
Findings
For validation, it is shown that reduction of 1.1%–12.5% in pollution and 8.8%–34.8% in total cost are achieved, as compared with literature. Also, the suggested operation strategy of PEVs parking and hydro storage results in reducing the total cost by 6.21%.
Originality/value
DR programs such as PEV parking play a major role in smart grid developments. Also, energy storage systems such as hydro storage lead to better performance of distributed generations and lower costs and pollution by thermal units. However, based on the literature, the effects of PEV parking and hydro storage on smart grid operation strategy are not considered. Therefore, contributions of this study are: effects of hydro storage on the smart grid are considered, effects of PEV parking on the smart grid are considered, a heuristic algorithm is developed to solve operation strategy problem for PEV parking and hydro storage in a smart grid environment.
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Vesna Rubežić, Luka Lazović and Ana Jovanović
The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model.
Abstract
Purpose
The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model.
Design/methodology/approach
The J-A model has five parameters which are assigned with physical meaning and whose determination is demanding. To determine these parameters, the fitness function, which represents the difference between the measured and the modeled hysteresis loop, is formed. Optimal parameter values are the values that minimize the fitness function.
Findings
The parameters of J-A model for three magnetic materials are determined. The model with the optimal parameters is validated using measured data and comparison with particle swarm optimization algorithm, genetic algorithm, pattern search and simulated annealing algorithm. The results show that the proposed method provides better agreement between measured and modeled hysteresis loop than other methods used for comparison. The proposed method is also suitable for simultaneous optimization of multiple hysteresis loops.
Originality/value
Chaotic optimization method is implemented for the first time for J-A model parameter identification. Numerical comparisons with results obtained with other optimization algorithms demonstrate that this method is a suitable alternative in parameters identification of J-A hysteresis model. Furthermore, this method is easy to implement and set up.
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Yogambari Venkatesan and Aravindhababu Palanivelu
The purpose of the paper is to develop a simple, efficient and robust power flow (PF) method for ill-conditioned distribution networks (DNs).
Abstract
Purpose
The purpose of the paper is to develop a simple, efficient and robust power flow (PF) method for ill-conditioned distribution networks (DNs).
Design/methodology/approach
It first formulates the PF problem as an optimization problem of minimizing the node power mismatches, while treating the corrections of node voltages as problem variables and then uses soccer game optimization (SGO), an artificial intelligent algorithm simulating the behavior of soccer game players in scoring goals, in solving the formulated PF problem.
Findings
It studies the performances of the developed method on four standard test DNs and exhibits that the method is superior in respect of accuracy, robustness and computational speed than those of existing methods.
Originality/value
It suggests a novel and new PF method using SGO and portrays that the proposed method is as accurate as any other PF method, robust like non-Newton type of PF methods and faster than Newton type of PF methods.
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Souhil Mouassa and Tarek Bouktir
In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single…
Abstract
Purpose
In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems.
Design/methodology/approach
A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed.
Findings
Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions.
Originality/value
The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.