Iranian Journal of Electrical and Electronic Engineering
Volume:16 Issue: 4, Dec 2020

It is very difficult and expensive to replace sensor node battery in wireless sensor network in many critical conditions such as bridge supervising, resource exploration in hostile locations, and wildlife safety, etc. The natural choice in such situations is to maximize network lifetime. One such approach is to divide the sensing area of wireless sensor network into clusters to achieve high energy efficiency and to prolong network lifetime. In this paper, an Artificial Bee Colony Inspired Clustering Solution (ABCICS) is introduced. The proposed protocol selects the head of the cluster with optimal fitness function. The fitness function comprises the residual energy of node, node degree, node centrality, and distance from base station to node. When cluster-head with high energy node transmits the data to the base station, it further minimizes the energy consumption of the sensor network. The presented protocol is compared with LEACH, HSA-PSO, and MHACO-UC. Simulation experiments show the effectiveness of our approach to enhance the network lifetime.

The Markov random field (MRF) theory has been accepted as a highly effective framework for designing noise-tolerant nanometer digital VLSI circuits. In MRF-based design, proper feedback lines are used to control noise and keep the circuits in their valid states. However, this methodology has encountered two major problems that have limited the application of highly noise immune MRF-based circuits. First, excessive hardware overhead that imposes a great cost, power consumption and propagation delay on the circuits and second, separate implementation of feedback lines that adds further delay to the circuits. In this paper, we propose a novel approach for minimal-cost inherent-feedback implementation of low-power MRF-based logic gates. The simulation results, which are based on 32nm BSIM4 models, demonstrate that besides excellent noise immunity of the proposed method, it has the least propagation delay in comparison with all of the previously reported MRF-based gates due to its inherent feedbacks. In addition, the proposed method outperforms competing ones, which have comparable noise immunity, in other circuit metrics like cost and power consumption. Specifically, the proposed method achieves at least 18%, 29%, and 39% reductions in cost, delay and power consumption with considerable noise immunity improvement compared with competing methods.

The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome these problems. The proposed method uses an adaptive unscented Kalman filter (AUKF) filter to generate the proposal distribution, in which the covariance of the measurement and process of the state are online adjusted by predicted residual as an adaptive factor based on a covariance matching technique. In addition, it uses the genetic operators based strategy to further improve the particle diversity. The results show the effectiveness of the proposed approach.

In order to enhance the accuracy of the motion vector (MV) estimation and also reduce the error propagation issue during the estimation, in this paper, a new adaptive error concealment (EC) approach is proposed based on the information extracted from the video scene. In this regard, the motion information of the video scene around the degraded MB is first analyzed to estimate the motion type of the degraded MB. If the neighboring MBs possess uniform motion, the degraded MB imitates the behavior of neighboring MBs by choosing the MV of the collocated MB. Otherwise, the lost MV is estimated through the second proposed EC technique (i.e., IOBMA). In the IOBMA, unlike the conventional boundary matching criterion-based EC techniques, not only each boundary distortion is evaluated regarding both the luminance and the chrominance components of the boundary pixels, but also the total boundary distortion corresponding to each candidate MV is calculated as the weighted average of the available boundary distortions. Compared with the state-of-the-art EC techniques, the simulation results indicate the superiority of the proposed EC approach in terms of both the objective and subjective quality assessments.

Increased popularity of digital media and image editing software has led to the spread of multimedia content forgery for various purposes. Undoubtedly, law and forensic medicine experts require trustworthy and non-forged images to enforce rights. Copy-move forgery is the most common type of manipulation of digital images. Copy-move forgery is used to hide an area of the image or to repeat a portion in the same image. In this paper, a method is presented for detecting copy-move forgery using the Scale-Invariant Feature Transform (SIFT) algorithm. The spearman relationship and ward clustering algorithm are used to measure the similarity between key-points, also to increase the accuracy of forgery detection. This method is invariant to changes such as rotation, scale change, deformation, and light change; it falls into the category of blind forgery detection methods. The experimental results show that with its high resistance to apparent changes, the proposed method correctly detects 99.56 percent of the forged images in the dataset and reveals the forged areas.

Multiplication is a basic operation in any signal processing application. Multiplication is the most important one among the four arithmetic operations like addition, subtraction, and division. Multipliers are usually hardware intensive, and the main parameters of concern are high speed, low cost, and less VLSI area. The propagation time and power consumption in the multiplier are always high. The multiplier speed usually determines the speed of the processor. Hence in this work, a design of a 32-bit multiplier is proposed by modifying the conventional shift-add multiplier. The proposed structure reduces the power consumed by the technique of minimizing the switching activities in the design. A 32-bit parallel prefix adder based on the modified Ling equation is also proposed to speed up the addition of the partial products in the multiplier. The design is modeled in VHDL and implementation is carried out in CADENCE software with 90 nm and 180 nm CMOS technology.

Using ANSYS finite element (FE) package, a multi-physics simulation model based on finite element method (FEM) is introduced for the multi-layer switched reluctance motor (SRM) in the present paper. The simulation model is created totally in ANSYS parametric design language (APDL) as a parametric model usable for various conventional types of this motor and it is included electromagnetic, thermal, and structural analyses. The static characteristic of flux-linkage with a phase, phase current waveform, instantaneous torque, and electromagnetic losses are predicted using the developed electromagnetic model. Carrying out 3D FE thermal analysis, the temperature rise due to the calculated core and copper losses is predicted in the developed thermal model. The transient, modal and harmonic analyses are done in the introduced structural model to determine the mode shapes, natural frequencies, displacement, and sound pressure level (SPL) in both time and frequency domains. In order to evaluate the developed simulation model, it is applied to a typical multi-layer SRM, and simulation results related to all the above-mentioned analyses are presented.

The hybrid AC-DC microgrid (HMG) architecture has the merits of both DC and AC coupled structures. Microgrids are subject to intermittence when the renewable sources are used. In the HMG, since power fluctuations occur on both subgrids due to varying load and unpredictable power generation from renewable sources, proper voltage and frequency regulation is the critical issue. This article proposes a unique method for operating a microgrid (MG) comprising of PV array, wind energy system (WES), fuel cell (FC), and battery in HMG configuration. The control scheme of the interlinking converter (ILC) regulates frequency, voltage, and power flow amongst the subgrids. Power management in the HMG is investigated under different scenarios. Proper power management is accomplished within the individual subgrids and among the subgrids by the control techniques adopted in the HMG. The system voltage and frequency deviations are found to be minimized when the FC system acts as the backup source for DC subgrid, reducing the power flow through the ILC.

The main purposes of a transformerless grid-connected photovoltaic (PV) system consist of the reduction of leakage current, extraction of maximum power point (MPP), tracking of MPP (MPPT), controlling the active and reactive powers, and having the unity power factor. To achieve the above-mentioned aims, the following actions have been performed in this paper. First of all, a brief analysis of the transformerless PV system has been done by using the conventional full-bridge (FB) topologies with two bipolar and unipolar PWM techniques. Then, an effective solution has been also introduced to significantly reduce the leakage current in the conventional H5 FB topology. Moreover, a proper control method has been proposed by using the combination of the fractional open-circuit voltage (FOCV) and the model predictive control (MPC) strategies to extract the MPP from PV panels, control the injection of the reactive power to the gird and have the unity power factor. At last, the simulation results performed in PSCAD software will be used to prove the correct performance of the proposed control method in the improved H5 FB topology.

This paper presents a pattern recognition-based scheme for detection of islanding conditions in synchronous- based distributed generation (DG) systems. The main idea behind the proposed scheme is the use of spatial features of system parameters such as the frequency, magnitude of positive sequence voltage, etc. In this study, the system parameters sampled at the point of common coupling (PCC) were analyzed using reduced-noise morphological gradient (RNMG) tool, first. Then, the spatial features of the RNMG magnitudes were calculated. Next, to optimize and increase the ability of the proposed scheme for islanding detection, the best features with a much discriminating power were selected based on separability index (SI) calculation. Finally, to distinguish the islanding conditions from the other normal operation conditions, a support vector machine (SVM) classifier was trained based on the selected features. To investigate the power of the proposed scheme for islanding detection, the results of examinations on the various islanding conditions including system loading and grid operating state were presented.  These results show that the proposed algorithm reliably detect the islanding condition within 32.7 ms.

The main objective of this paper is to model and optimize the parallel and relatively complex FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) controller for simultaneous control of the voltage and frequency of a micro-grid in the islanded mode. The FP+FI+FD controller has three parallel branches, each of which has a specific task. Finally, as its name suggests, the final output of the controller is derived from the algebraic summation of the outputs of these three branches. Combining the basic features of a simple PID controller with fuzzy logic that leads to an adaptive control mechanism, is an inherent characteristic of the FP+FI+FD controller. This paper attempts to determine the optimal control gains and Fuzzy membership functions of the FP+FI+FD controller using an improved Salp swarm algorithm (ISSA) to achieve its optimal dynamic response. The time-domain simulations are carried out in order to prove the superb dynamic response of the proposed FP+FI+FD controller compared to the PID control methods. In addition, a multi-input-multi-output (MIMO) stability analysis is performed to ensure the robust control characteristic of the proposed parallel fuzzy controller.

In this work, a robust nonlinear control technique of a doubly fed induction generator (DFIG) intended for wind energy systems has been proposed. The principal idea in this article is to decouple the active and reactive power of the DFIG with high robustness using the backstepping strategy. The principle of this control method is based on the Lyapunov function, in order to guarantee the global asymptotic stability of the system. Finally, we present some simulation results in order to verify the efficiency and robustness of the proposed control technique.

The development of communications and telecommunications infrastructure, followed by the extension of a new generation of smart distribution grids, has brought real-time control of distribution systems to electrical industry professionals’ attention. Also, the increasing use of distributed generation (DG) resources and the need for participation in the system voltage control, which is possible only with central control of the distribution system, has increased the importance of the real-time operation of distribution systems. In real-time operation of a power system, what is important is that since the grid information is limited, the overall grid status such as the voltage phasor in the buses, current in branches, the values of loads, etc. are specified to the grid operators. This can occur with an active distribution system state estimation (ADSSE) method. The conventional method in the state estimation of an active distribution system is the weighted least squares (WLS) method. This paper presents a new method to modify the error modeling in the WLS method and improve the accuracy SVs estimations by including load variations (LVs) during measurement intervals, transmission time of data to the information collection center, and calculation time of the state variables (SVs), as well as by adjusting the variance in the smart meters (SM). The proposed method is tested on an IEEE 34-bus standard distribution system, and the results are compared with the conventional method. The simulation results reveal that the proposed approach is robust and reduces the estimation error, thereby improving ADSSE accuracy compared with the conventional methods.