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27,762 Article Results

Experimental Analysis of Factors Affecting the Power Output of the PV Module

10.11591/ijece.v7i6.pp3190-3197
Arjyadhara Pradhan , Bhagbat Panda
Energy is the driving force in all the sectors as it acts like an index of standard of living or prosperity of the people of the country. However heavy dependence on fossil fuels leads to global warming, hence there is a need for the use of clean, sustainable, and eco friendly form of energy. Among the various types of non-conventional energy solar energy is the fundamental as it is abundant, pollution free and universally available.Even though the main input to the PV system is the solar radiation still there are other factors which affects the efficiency of the pv module. In this paper real time experiment has been conducted to analyze the effect of various factors like irradiance, temperature, and angle of tilt, soiling, shading on the power output of the pv module. Temperature is a negative factor which reduces the efficiency of the module and can be reduced by various cooling arrangements. Presence of dust particles and shading obstructs the incident solar radiations entering the panel and the effect is seen in the iv and pv curve .For better performance solar tracking at maximum power point is suggested to improve the power output of the pv module.
Volume: 7
Issue: 6
Page: 3190-3197
Publish at: 2017-12-01

Hardware Implementation of Solar Photovoltaic System based Half Bridge Series Parallel Resonant Converter for Battery Charger

10.11591/ijpeds.v8.i4.pp1622-1630
Rakhi K , Ilango Karuppasamy , Manjula G Nair
The long established battery chargers are having many drawbacks such as prominent ripple charging current, less efficiency and bulky in size. To overcome these drawbacks of conventional battery charger, several charging circuits have been proposed and inevitability force to design a high-performance battery charger with small in size and improved efficiency. In this paper solar photovoltaic system based half-bridge series–parallel resonant converter (HBSPRC) charger is proposed for battery interface. The converter is designed to abolish low and high-frequency ripple currents and thus take full advantage of the life of secondary battery circuit. This is achieved by designing converter switches turn on at zero current and zero voltage with switching frequency greater than that of resonance frequency which leads to freewheeling diodes need not have very fast reverse-recovery characteristics. The performance of the power converters depends upon the control method adopted; in this work fuzzy logic controller is used for controlling the output voltage of HBSPRC. The fuzzy control scheme for the HBSPR converter has been designed and validated in hardware implementation of HBSPRC switching technique.  From the results, it is found that the proposed battery charging system which reduces the switching loss and voltage stress across the power switches which increases the efficiency of the converter.
Volume: 8
Issue: 4
Page: 1622-1630
Publish at: 2017-12-01

Density Based Clustering with Integrated One-Class SVM for Noise Reduction

10.11591/ijict.v6i3.pp199-208
K. Nafees Ahmed , T. Abdul Razak
Information extraction from data is one of the key necessities for data analysis. Unsupervised nature of data leads to complex computational methods for analysis. This paper presents a density based spatial clustering technique integrated with one-class Support Vector Machine (SVM), a machine learning technique for noise reduction, a modified variant of DBSCAN called Noise Reduced DBSCAN (NRDBSCAN). Analysis of DBSCAN exhibits its major requirement of accurate thresholds, absence of which yields suboptimal results. However, identifying accurate threshold settings is unattainable. Noise is one of the major side-effects of the threshold gap. The proposed work reduces noise by integrating a machine learning classifier into the operation structure of DBSCAN. The Experimental results indicate high homogeneity levels in the clustering process.
Volume: 6
Issue: 3
Page: 199-208
Publish at: 2017-12-01

Predictive Direct Power Control (PDPC) of Grid-connected Dual-active Bridge Multilevel Inverter (DABMI)

10.11591/ijpeds.v8.i4.pp1524-1533
H.H. Goh , Azuwien Aida , S.S. Lee , S.Y. Sim , K.C. Goh
This paper deals with controlling a grid-connected dual-active bridge multilevel inverter for renewable energy integration. The concept of direct power control is integrated with model predictive control algorithm, which is termed as predictive direct power control, to control the real and reactive power injected into the power grid. The proposed multilevel inverter allows more options of feasible voltage vectors for switching vector selections in order to generate multilevel outputs, and thereby obtaining high power quality in the power grid. By using the predictive direct power control, simulation results show that the proposed multilevel inverter produces lower power ripple and manage to achieve currents with low total harmonic distortion which are well within the IEEE standard. The modeling and simulation of the system are implemented and validated by MATLAB Simulink software.
Volume: 8
Issue: 4
Page: 1524-1533
Publish at: 2017-12-01

Software Aging Forecasting Using Time Series Model

10.11591/ijeecs.v8.i3.pp589-596
I M Umesh , G N Srinivasan , Matheus Torquato
With the emergence of virtualization and cloud computing technologies, several services are housed on virtualization platform. Virtualization is the technology that many cloud service providers rely on for efficient management and coordination of the resource pool. As essential services are also housed on cloud platform, it is necessary to ensure continuous availability by implementing all necessary measures.  Windows Active Directory is one such service that Microsoft developed for Windows domain networks. It is included in Windows Server operating systems as a set of processes and services for authentication and authorization of users and computers in a Windows domain type network. The service is required to run continuously without downtime. As a result, there are chances of accumulation of errors or garbage leading to software aging which in turn may lead to system failure and associated consequences. This results in software aging. In this work, software aging patterns of Windows active directory service is studied. Software aging of active directory needs to be predicted properly so that rejuvenation can be triggered to ensure continuous service delivery. In order to predict the accurate time, a model that uses time series forecasting technique is built.
Volume: 8
Issue: 3
Page: 589-596
Publish at: 2017-12-01

Feature Selection Using Evolutionary Functional Link Neural Network for Classification

10.11591/ijaas.v6.i4.pp359-367
Amaresh Sahu , Sabyasachi Pattnaik
Computational time is high for Multilayer perceptron (MLP) trained with back propagation learning algorithm (BP) also the complexity of the network increases with the number of layers and number of nodes in layers. In contrast to MLP, functional link artificial neural network (FLANN) has less architectural complexity, easier to train, and gives better result in the classification problems. The paper proposed an evolutionary functional link artificial neural network (EFLANN) using genetic algorithm (GA) by eliminating features having little or no predictive information. Particle swarm optimization (PSO) is used as learning tool for solving the problem of classification in data mining.  EFLANN overcomes the non-linearity nature of problems by using the functionally expanded selected features, which is commonly encountered in single layer neural networks. The model is empirically compared to MLP, FLANN gradient descent learning algorithm, Radial Basis Function (RBF) and Hybrid Functional Link Neural Network (HFLANN) . The results proved that the proposed model outperforms the other models.
Volume: 6
Issue: 4
Page: 359-367
Publish at: 2017-12-01

Comparative Study of Various Neural Network Architectures for MPEG-4 Video Traffic Prediction

10.11591/ijaas.v6.i4.pp283-292
J.P. Kharat
Network traffic as it is VBR in nature exhibits strong correlations which make it suitable for prediction. Real-time forecasting of network traffic load accurately and in a computationally efficient manner is the key element of proactive network management and congestion control. This paper comments on the MPEG-4 video traffic predictions evaluated by different types of neural network architectures and compares the performance of the same in terms of mean square error for the same video frames. For that three types of neural architectures are used namely Feed forward, Cascaded Feed forward and Time Delay Neural Network. The results show that cascade feed forward network produces minimum error as compared to other networks. This paper also compares the results of traditional prediction method of averaging of frames for future frame prediction with neural based methods. The experimental results show that nonlinear prediction based on NNs is better suited for traffic prediction purposes than linear forecasting models.
Volume: 6
Issue: 4
Page: 283-292
Publish at: 2017-12-01

Maximum Power Point Tracking for a Grid Connected Photovoltaic System using Sliding Mode Control

10.11591/ijpeds.v8.i4.pp1785-1792
D. Sattianadan , V. Kalyanasundaram , S. Vidyasagar , Deepak Kumar Nayak , Roopam Jha
This paper presents a method to track the maximum power point for an isolated grid connected photovoltaic system. The method used to achieve this goal is sliding mode control. A high frequency flyback converter topology working in continuous conduction mode is used to boost the voltage and also provides galvanic isolation between input and output side. An inverter is used to invert the power for a grid connected operation. Therefore, the primary objective of this study is to design a sliding mode controller which can track maximum power driving a high frequency flyback converter and demonstrate its practicality as a higly efficient maximum power point tracker. This system is modelled and tested in MATLAB SIMULINK. To verify the results a practical implementation of sliding mode controller with high frequency flyback transformer is performed in a hardware setup
Volume: 8
Issue: 4
Page: 1785-1792
Publish at: 2017-12-01

FOPID Controlled Three Stage Interleaved Boost Converter Fed DC Motor Drive

10.11591/ijpeds.v8.i4.pp1771-1775
M.L Bharathi , D. Kirubakaran
Three stage Interleaved boost converter is a good choice between DC source and DC motor. This work deals with enhancement of response of three stage ILBC fed DC motor drive system using FOPID controller. Closed loop ILBCDCM systems controlled by PI & FOPID are modeled and simulated. The results are presented for PI & FOPID controlled ILBCDCM systems. The comparison of response is done in terms of settling time and steady state error in speed of ILBCDCM. The results indicate that FOPID controlled ILBCDCM gives better response than PI controlled ILBCDCM system.
Volume: 8
Issue: 4
Page: 1771-1775
Publish at: 2017-12-01

A Fuzzy Logic Based Mppt Controller For Wind-Driven Three-Phase Self-Excited Induction Generators Supplying Dc Microgrid

10.11591/ijaas.v6.i4.pp325-334
B.Murali Mohan , M.Pala Prasad Reddy , M. Lakshminarayana
In this paper, a straightforward strategy for tracking the maximum power (MP) accessible in the wind energy conversion system for dc microgrid is proposed. A three-phase diode bridge rectifier alongside a dc-dc converter has been utilized between the terminals of wind-driven induction generator and dc microgrid. Induction generator is being worked in self-energized mode with excitation capacitor at stator. The output current i.e., dc grid current act as a control variable to track the MP in the proposed WECS. In this manner, the proposed calculation for maximum power point tracking (MPPT) is autonomous of the machine and wind-turbine parameters. Further, a technique has been created for deciding the obligation proportion of the dc-dc converter for working the proposed system in MPPT condition utilizing wind turbine qualities, relentless state proportionate circuit of prompting generator and power balance in power converters. Circuit straightforwardness and basic control calculation are the significant points of interest of the proposed setup for supplying energy to the dc microgrid from WECS. The fruitful working of the proposed calculation for Fuzzy logic based  MPPT has been shown with broad exploratory results alongside the simulated values.
Volume: 6
Issue: 4
Page: 325-334
Publish at: 2017-12-01

Classification of Content based Medical Image Retrieval Using Texture and Shape feature with Neural Network

10.11591/ijaas.v6.i4.pp368-374
Sweety Maniar , Jagdish S. Shah
Medical image classification and retrieval systems have been finding extensive use in the areas of image classification according to imaging modalities, body part and diseases. One of the major challenges in the medical classification is the large size images leading to a large number of extracted features which is a burden for the classification algorithm and the resources. In this paper, a novel approach for automatic classification of fundus images is proposed. The method uses image and data pre-processing techniques to improve the performance of machine learning classifiers. Some predominant image mining algorithms such as Classification, Regression Tree (CART), Neural Network, Naive Bayes (NB), Decision Tree (DT) K-Nearest Neighbor. The performance of MCBIR systems using texture and shape features efficient. . The possible outcomes of a two class prediction be represented as True positive (TP), True negative (TN), False Positive (FP) and False Negative (FN).
Volume: 6
Issue: 4
Page: 368-374
Publish at: 2017-12-01

Improved Color Satellite Image Segmentation Using Tsallis Entropy and Granular Computing

10.11591/ijaas.v6.i4.pp293-302
Jagan kumar. N , Agilandeeswari. L , Prabukumar. M
The research work is to improve the segmentation of the color satellite images. In this proposed method the color satellite image can be segmented by using Tsallis entropy and granular computing methods with the help of cuckoo search algorithm. The Tsallis and granular computing methods will used to find the maximum possibility of threshold limits and the cuckoo search will find the optimized threshold values based on threshold limit that is calculated by the Tsallis entropy and granular computing methods and the multilevel thresholding  will used for the segmentation of color satellite images based on the optimized threshold value that will find by this work and these methods will help to select the optimized threshold values for multiple thresholding effectively.
Volume: 6
Issue: 4
Page: 293-302
Publish at: 2017-12-01

Comparison of Modeling and Simulation results Management Micro Climate of the Greenhouse by Fuzzy Logic between a Wetland and Arid region

10.11591/ijaas.v6.i4.pp335-342
Didi Faouzi , N. Bibi-Triki , B. Draoui , A. Abène
Currently the climate computer offers many benefits and solves problems related to the regulation, monitoring and controls. Greenhouse growers remain vigilant and attentive, facing this technological development. they ensure competitiveness and optimize their investments / production cost which continues to grow. The application of artificial intelligence in the industry known for considerable growth, which is not the case in the field of agricultural greenhouses, where enforcement remains timid. it is from this fact, we undertake research work in this area and conduct a simulation based on meteorological data through MATLAB Simulink to finally analyze the thermal behavior -greenhouse microclimate energy . In this paper we present comparison of modeling and simulation management of the greenhouse microclimate by fuzzy logic between a wetland  (Dar El Beida Algeria) and the other arid (Biskra Algeria).
Volume: 6
Issue: 4
Page: 335-342
Publish at: 2017-12-01

A Novel Approach for Space Vector Based PWM Algorithm for Diode Clamped Three level VSI Fed Induction Motor Drive

10.11591/ijpeds.v8.i4.pp1534-1547
Debanjan Roy , Madhu Singh , Tapas Roy
Performance of a voltage source inverter depends on pulse width modulation algorithms. Various algorithms exist for conventional space vector as well as space vector based bus clamped pulse width modulation for multilevel inverter in the literature. In this paper appropriate region selection algorithm for conventional space vector pulse width modulation (CSVPWM) and bus clamped pulse width modulation (BCPWM) techniques are proposed for diode clamped three level voltage source inverter. The proposed techniques are implemented on a three level voltage source inverter fed induction motor drive for open loop operation. The schemes are simulated in MATLAB/SIMULINK environments. The merit of proposed region selection algorithm is tested and verified through simulation result. Further performance comparisons between SVPWM and BCPWM for different modulation index are discussed. 
Volume: 8
Issue: 4
Page: 1534-1547
Publish at: 2017-12-01

Review of Machine Vision Based Insulator Inspection Systems for Overhead Power Distribution System

10.11591/ijaas.v6.i4.pp303-312
P. Surya Prasad , B. Prabhakara Rao
The necessity to have reliable and quality power distribution is increasing, and hence there is great scope for research on automation of distribution system. There are signs of increased research in the work on condition monitoring of insulators during the last few decades. The possible failures can be predicted before they actually occur by using the condition monitoring of cables or any electrical equipment on-line. Those assets such as towers, conductors and insulators which are on the threshold of failure have to be replaced or repaired, so that forced outages reduce. Traditionally the workers who inspect these lines check them in close proximity by going for foot-patrolling and pole-climbing. With an incredible expansion of power distribution network even to remote areas, previously mentioned methods do not seem to be viable. In developed countries aerial patrolling has been adopted to monitor the insulators as an alternative. The development of an efficient method of condition monitoring by using image processing followed by machine learning techniques is found to be a suitable method and thus emerging as a feasible option for real-time implementation. This review paper covers overall aspects of automatic detection of defects of insulator systems of electric power lines and classification into different classes by using vision-based techniques.
Volume: 6
Issue: 4
Page: 303-312
Publish at: 2017-12-01
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