Majlesi Journal of Electrical Engineering
Volume:12 Issue: 2, Jun 2018

This article presents a network reconfiguration in balanced distribution networks using Multi Verse Optimization (MVO) to optimize the total system resistive losses and reduce emissions by means of step by step switching. Reconfiguration is a considerable manner of altering the power flows through the lines from the main substation to load ends, while maintaining radial structure. The main objective of this paper is to solve feeder reconfiguration problem to reduce the total line losses and emission reduction for an open loop distribution system. MVO is a population based method to resolve the network reconfiguration problem. A precise power flow solution is applied and the objective is formulated. A nature inspired Multi Verse Optimization is utilized to restructure the power distribution system and identify the optimal tie switches for lowest line losses in the distribution network. The reduction of resistive losses leads to reduction of emissions. The suggested MVO method has carried out on two standard 16-node and 69-node distribution systems for normal load and overload conditions and results show the performance of the anticipated MVO method. The final outcomes prove that a significant reduction in real power losses and emissions.

This paper investigates the dynamic performance and the stability of synchronous reference frame phase-locked loop (SRF-PLL) influenced by microgrid and network-side parameters. Given that the stability of PLL affected by microgrid-side parameters has not been yet studied, this article aims at evaluating this issue after a detailed analytical modeling of microgrid components (including the production power fluctuations, energy storage system, microgrid-side loads, controller parameters etc.). In addition, through a proposed criterion for stability of PLL, the optimized rate of microgrid and network parameters is obtained using simulation results and statistical methods. First, the model of the mentioned microgrid is simulated in MATLAB software. Then, a Taguchi approach is employed in order to gather simulation results. Finally, the best sets of microgrid and network parameters that lead to the stability of PLL are determined.

The voltage source inverter fed induction motor drive produces pulsating torque due to harmonics present in the output voltage of the inverter. Therefore reduction of harmonics is the major concern in any power converter fed ac drives. In this paper, a harmonic reduction technique for four pole induction motor drive is presented. A modified carrier based space vector PWM technique with suitable phase shift between modulating and carrier waves used to cancel the harmonic content in the output voltage. In order to use this PWM technique, stator winding of the four pole induction motor is disconnected exactly at middle and each part of the winding is fed with two two-level inverters from both the sides. All these two-level inverters are supplied by two isolated dc sources to avoid the path for zero sequence currents. By using proposed PWM technique to the inverter configuration, all lower order harmonics are shifted to four times switching frequency. The proposed concept is tested with 5hp four-pole induction motor in MATLAB/Simulink and experimentally also verified with laboratory prototype. Simulation and experimental results show the effectiveness of the proposed topology in complete linear modulation region and also demonstrate the improvement in harmonic profile.

The usage of energy storage units in power system will reduce frequency oscillations immediately subjected to random load changes. In this project, investigations are carried out for an isolated power system with ALFC unit and isolated power system with mutual coupling effects. In each case the effect of different storage units are studied for random load changes. Here particle swarm optimization algorithm (PSO) and improved particle swarm optimization technique (IPSO) are used to tune the parameters of storage units to provide proper control strategy for the system. Instead of using two flexible storage devices, here one flexible storage unit is considered with constant storage system. Results are carried out in MATLAB/SIMULINK software.

This paper objective presents static synchronous series compensation FACTS device with biogeography based optimization (BBO) to deal for obtaining worthwhile power flow control. The biogeography based optimization method is utilized to find the optimal fitted child sets by surviving parents with the help of migration and mutation process. The present BBO technique from the evolutionary strategy with static synchronous series compensator provides improved outcomes in comparison to other optimization methods. The simulation outcomes illustrate that the proposed BBO algorithm is efficacious, secure and correct to search the optimized values with SSSC based FACTS devices. The proposed method is considering the solution quality appears to be an optimistic substitute method for extricating the OPF problems. The simplification and effectiveness of this method are validated on the IEEE 57 bus and 75 bus Systems. In this paper, from the outcome results, it is clearly show that the proposed technique execution properly and can effectively apply to the optimal position of multiple OPF problems. i.e. BBO based algorithm with SSSC FACTS device is found better results when compared to without SSSC device in all aspects.

Hybrid Energy Storage System (HESS) has been implemented for better energy efficiency to Hybrid/Electric Vehicles (HEV/EV), in that the main source is Battery and UltraCapacitor (UC) is the auxiliary source. The battery is connected to DC Bus through Boost Converter and UltraCapacitor has connected through Buck-Boost Converter. Battery and UltraCapacitor voltages levels are maintained less than the DC bus voltage. The main aim of this paper is to design an intelligent controller for a smooth transition between the sources in the Hybrid Energy Storage System. Math Function Based (MFB) Controller has modelled and implemented to an electric motor for Electric/Hybrid Electric Vehicle Application. The MFB controller has to work based on the Speed of the motor and this controller makes the closed loop operation of the overall system with smooth operation between the energy sources. Proportional Integral (PI) controller used here to maintain the constant voltage profile for various loads at the terminals of the electric motor. Combination of PI and MFB controllers has given closed loop operation of the entire model with smooth switching between the sources. The total circuit has simulated in MATLAB/Simulink and obtained the satisfactory results, which are discussed in the results section.

This paper includes a novice technique for locating single line to ground fault in electrical transmission network. Validation of the proposed algorithm is demonstrated using matlab simulink. Simpower system tool box is used for the modeling of smart meter, transmission lines and single line to ground fault (1L-G). A novel method is proposed to countercheck whether the fault has occurred really or not. Data related to 1l-G fault has been collected at 220kV Lonikand substation and analyzed. c exclusively during the visit at Kalkitech (top manufacturing company of Intelligent Electronic Devices (IEDs) in Bangalore, Karnataka, India). Effect of harmonics on fault current measurement using smart meter is elaborated. Advancements in communication technology are illustrated from asset management perspective.

Sentiment analysis automatically classifies the opinions, which are expressed in a document, usually as positive or negative. A review document in general, reflects its author’s opinion about the objects mentioned in the text. Therefore, it can have many useful applications such as opinionated web search and automatic analysis of reviews. Although sentiment analysis is a kind of text classification problem, structures of review documents are different from texts like news, articles, or web pages; so that techniques applied for text classification are needed to be re-experimented for the sentiment analysis. Assigning appropriate weights to features is important to the performance of sentiment analysis so that important features can receive higher weights for the feature vectors. Feature selection reduces feature vector size by eliminating redundant or irrelevant features to improve classification accuracy. In this study, our aim is to examine the effects of term weighting methods on newly proposed Query Expansion Ranking (QER) feature selection method and also compare the classification results with one of the well-known feature selection method namely Chi-square statistic. We use three popular term weighting methods (i.e., term presence, term frequency, term frequency and inverse document frequency-tf*idf) and perform experiments using multinomial Naïve Bayes classifier. The experimental results show that when QER feature selection method is used with tf*idf term weighting method, the classification performance improves in terms of F-score.

In parallel with the rapid development of automation systems, there is a growing need to perceive different physical quantities in the industry. Various sensors have been developed to meet this need. Be affordable sensors, in terms of investment costs of systems and maintenance as well as repair costs are gaining importance. One of the commonly used sensors in automation is colour sensors. Colour sensors are frequently used in production lines especially for detecting defective products. Two general methods are used in colour sensors. The first of these methods is performed by camera and video processing microcontroller however this method is costly. Another method is the use of light source and LDR or phototransistor. The sensors produced by this method are more cost effective. These sensors have different types. In this study, a simple colour sensor was obtained by using white light source and three LDRs coated with red, green, blue film as well as arduino uno. The results obtained are compared with the RGB colour code table. In this way, the construction of a simple colour sensor has been studied in detail.

In this paper, thin dipole is investigated in the 3.1-10.6 GHz Ultra-Wide Band frequency range. The study includes the design of half wave dipole antenna with different dipole radii to improve the antenna characteristics. Antenna parameters including return loss, Voltage Standing Wave Ratio, -10 dB bandwidth and radiation pattern are examined according to Federal Communication Commission regulations and Ultra-Wide Band system requirements in this frequency range. Additionally, two optimization techniques, Genetic Algorithm and Particle Swarm Optimization are applied to obtain the best dipole radius. CST Microwave Studio, an electromagnetic simulation program, is used for the design of the antenna structure and the simulation purposes. The simulation is performed in transient mode. The results show that the antenna performance can be improved by selecting the suitable antenna dimensions. Additionally, Genetic Algorithm and Particle Swarm Optimization techniques are compared in terms of time consumption to obtain the best VSWR and return loss values. The results also depict that Genetic Algorithm yields better results for the proposed structure.

Wireless sensor networks (WSNs) contains an enormous number of sensor nodes deployed in huge numbers which are able to sense, process and transmit environmental data to the base station for plenty of applications. Clustering is one of the important issues for prolonging the network lifetime in wireless sensor networks. It includes grouping of sensor nodes into clusters and selecting cluster heads for all the clusters. Cluster heads collect the data from respective cluster’s nodes and forward the aggregated data to base station. Some important challenges in wireless sensor networks are to find optimal number of clusters, clustering and to select appropriate cluster heads. In this direction, we present a method that includes three phases. At first, the optimum number of clusters is calculated. In the second, clustering is done by use of k-means algorithm. In the last phase, it is presented a multi criteria decision-making approach for the selection of cluster heads. This approach is used to select cluster heads based on criteria including residual energy, the distance (the distance from the cluster and the distance from the base station), the number of neighbors (the one-step neighbor and the two-step neighbor), the centrality of the nodes and the number of times a node has been cluster head. We implement the proposed method in the NS2 environment and evaluate its effect and compare it with the NEECP and E-LEACH methods. The simulation results demonstrate that this approach is more effective in prolonging the network lifetime than the NEECP and E-LEACH methods in homogeneous environments.

Interline power flow controller (IPFC) is a concept of AC flexible control of the transmission system (FACTS), with the ability to series compensation and power flow management in multi lines of a post power. Out of all FACTS devices interline power flow converter (IPFC) is considered to be most flexible, powerful and versatile. IPFC has the capability of compensating multi-transmission line. The proper placement of interline power flow controller (IPFC) can improve the transmission line congestion problem to a great extent. This paper proposed, the optimal location of the IPFC in electrical power systems, using the particle swarm optimization algorithm. Expression of sample figure and analysis of the sample system shows that IPFC is effective to minimize the power losses in the power system.