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Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
Issue Info: 
  • Year: 

    2017
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    1-12
Measures: 
  • Citations: 

    0
  • Views: 

    1403
  • Downloads: 

    0
Abstract: 

Electric vehicles (EVs) are new and growing loads in distribution networks. Increasing number of electric vehicles in a distribution network causes increase of electricity energy demand. Therefore, in the absence of any energy consumption management, some distribution system operation constraints (e.g. bus voltage magnitude) may be violated. Power electronic devices used for charging and discharging the batteries, are usually called chargers.The charger could be unidirectional (transfer the energy from network to the battery) or bidirectional. Bidirectional chargers work in four areas of PQ power plane. In this paper, firstly, the active and reactive power management of smart distribution network using electric vehicles as non-linear problem is presented. Then, the problem is converted to mixed integer linear programming (MILP) problem using specific linearization method and is solved by GAMS package. The proposed scheme has been tested on the 33-bus distribution network and its performance and capability have been evaluated by simulation results.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Issue Info: 
  • Year: 

    2017
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    13-23
Measures: 
  • Citations: 

    0
  • Views: 

    847
  • Downloads: 

    0
Abstract: 

The purpose of this paper is to exploit the compressed sensing theory in order to compress multi-lead ECG channels with a high compression ratio and minimum reconstruction error. In order to obtain the sparse representation of the ECG signals a basis matrix with Gaussian kernels which have the maximum resemblance with ECG signals, is constructed. Then using Orthogonal matching pursuit, algorithm which is a greedy/iterative optimization technique, the sparse representation is acquired.Finally, utilizing the compressed sensing theory is possible. In order to prove the accuracy of the algorithm the same optimization technique is used to reconstruct the compressed signal. Using a wavelet basis is also common to obtain the sparse representation. The compressed sensing theory is also applied to the ECG signals for which their sparse representations have been obtained using a wavelet basis. The results show the superiority of the proposed method over the wavelet basis.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Issue Info: 
  • Year: 

    2017
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    25-39
Measures: 
  • Citations: 

    0
  • Views: 

    599
  • Downloads: 

    0
Abstract: 

In this paper, sparse double selective channel estimation using compressed sensing (CS) theory for OFDM systems is investigated. This theory helps to reduce the required pilot ratio and equivalently increases the spectral efficiency to achieve a constant mean square error. This is of great importance especially for double selective channels in which the required number of unknowns to be estimated and also the required number of pilot symbols are high. To take the advantage of compressed sensing, it is proposed that the sparsity enhancement of the coefficients of basis expansion model (BEM) should be considered in BEM design. It is also proposed to use K-SVD algorithm that is one of the most popular dictionary learning algorithms. Moreover, in this paper clustered pilot symbols are used to avoid inter-carrier interference. It is noteworthy that the channel coefficients representing intercarrier interference are also estimated to be used in equalization. Numerical experiments have shown that the compressed sensing estimator employing the proposed basis, outperforms the one employing DFT-DPSS in terms of NMSE and system BER.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View 599

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Issue Info: 
  • Year: 

    2017
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    41-54
Measures: 
  • Citations: 

    0
  • Views: 

    840
  • Downloads: 

    0
Abstract: 

This study presents a Fast Discrete S-Transform based method to discriminate internal fault currents of power transformer from other disturbances. A criterion function is proposed based on some extracted features from the obtained S-Matrix and frequency contours. First, the Support Vector Machine (SVM) is extended for feature classification. Then, the Bee optimization algorithm is implemented to select optimal parameters of SVM classifier. To do this, several conditions of external and internal faults, inrush current and different levels of current transformer saturation are simulated using PSCAD/EMTDC software. In addition, differential currents are contaminated by noise for modeling real conditions. To evaluate the performance of proposed scheme, the obtained results are compared with results of other methods. Comparing the results shows that the proposed method remains stable with high accuracy during transformer excitation and external faults. Also, the proposed approach is effective, fast and not affected by noise during classification of different events.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Issue Info: 
  • Year: 

    2017
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    55-69
Measures: 
  • Citations: 

    0
  • Views: 

    919
  • Downloads: 

    0
Abstract: 

Phase balancing and power losses are two significant problems in distribution networks. Rephasing technique is one solution for phase unbalancing. Reconfiguration is also used for power loss reduction and voltage profile improvement. While reconfiguration does not have a great effect on power loss reduction, in this paper a new method for simultaneous optimization of rephasing and reconfiguration problems in distribution networks are introduced to reduce phase unbalancing and power losses and improve the voltage profile. The greatest advantage of simultaneous optimization of rephasing and reconfiguration is a very low performing cost. Besides, optimal DG placement can reduce the power loss and improve voltage profile. As there are several objective functions, the objectives are fuzzified and integrated as the fuzzy multi-objective function. Eventually, by using the BF-SD algorithm, optimization of rephasing, reconfiguration and DG placement are simultaneously performed. At the end, the proposed method is applied to feeder No.3062 in Ahwaz, Iran.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View 919

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Issue Info: 
  • Year: 

    2017
  • Volume: 

    8
  • Issue: 

    2
  • Pages: 

    71-81
Measures: 
  • Citations: 

    0
  • Views: 

    888
  • Downloads: 

    0
Abstract: 

Computational intelligence techniques have a great potential to solve different computational problems in engineering sciences. In this paper, modeling and simulation of down hole drilling motor using the computational intelligence methods such as artificial neural network (ANN), radial basis function (RBF) and adaptive neuro-fuzzy inference system (ANFIS) is presented. Experimental data are used to train and test the proposed models. The results of the proposed models are compared with the experimental data. The predicated values are found to be in a good agreement with the experimental values. Also, they are very faster than the experimental measurement method. These compact models can reduce the computational time while keeping the accuracy of physics-based model and allow the fast and accurate system level simulation and modeling of industrial packages.Finally, using the proposed ANN model, which is the best proposed model, an equation to describe the nonlinear behavior of down hole drilling motor is introduced.

Yearly Impact: مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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