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28,428 Article Results

Chaos Embedded Symbiotic Organisms Search Technique for Optimal FACTS Device Allocation for Voltage Profile and Security Improvement

10.11591/ijeecs.v8.i1.pp146-153
Mohamad Khairuzzaman Mohamad Zamani , Ismail Musirin , Saiful Izwan Suliman , Tarek Bouktir
Due to the ever-increasing energy demand, power system operators have attempted to cope with these demands while keeping the power system remain operable. Economic constraints have forced the power system operator to abandon their effort in expanding the power system. The increased load demand can cause the power system to suffer from voltage instability and voltage collapse, especially during contingency condition. Hence, a strategy is required to maintain the steady state operation of a power system. Various research has been conducted to tackle this problem. Therefore, this paper presents the implementation of Chaos Embedded Symbiotic Organisms Search technique to solve optimal FACTS device allocation problem in power transmission system. Various practical constraints are also considered in the optimisation process to emulate the real-life constraints in power system. The optimisation process is conducted on a 26-bus IEEE RTS has validated that the results obtained has not violated the power system stability. The results provided by the proposed optimisation technique has successfully improved the voltage profile and voltage security in the system. Comparative studies are also conducted involving Particle Swarm Optimization and Evolutionary Programming technique resulting good results agreement and superiority of the proposed technique. Results obtained from this study would be beneficial to the power system operators regarding optimisation in power system operation for the implementation in real power transmission network.
Volume: 8
Issue: 1
Page: 146-153
Publish at: 2017-10-01

A Novel Integrated Framework to Ensure Better Data Quality in Big Data Analytics over Cloud Environment

10.11591/ijece.v7i5.pp2798-2805
C.S. Sindhu , Nagaratna P. Hegde
With advent of Big Data Analytics, the healthcare system is increasingly adopting the analytical services that is ultimately found to generate massive load of highly unstructured data. We reviewed the existing system to find that there are lesser number of solutions towards addressing the problems of data variety, data uncertainty, and data speed. It is important that an error-free data should arrive in analytics. Existing system offers single-hand solution towards single platform. Therefore, we introduced an integrated framework that has the capability to address all these three problems in one execution time. Considering the synthetic big data of healthcare, we carried out the investigation to find that our proposed system using deep learning architecture offers better optimization of computational resources. The study outcome is found to offer comparatively better response time and higher accuracy rate as compared to existing optimization technqiues that is found and practiced widely in literature.
Volume: 7
Issue: 5
Page: 2798-2805
Publish at: 2017-10-01

Power System State Estimation Bad Data Detection and Identification: A Review on Issues and Alternative Formulations

10.11591/ijeecs.v8.i1.pp122-128
Nurul Fauzana Imran Gulcharan , Nursyarizal Mohd Nor , Taib Ibrahim , Hanita Daud
State Estimation (SE) is the main function of power system where Energy Management System (EMS) is obliged to estimate the available states. Power system is a quasi-static system and hence changes slowly with time. Dynamic State Estimation (DSE) technique represents the time deviation nature of the system, which allows the forecasting of state vector in advance. Various techniques for DSE are available in the literature. This paper presents a review on different methodologies and developments in DSE, based on comprehensive survey of the available literature. From the survey it can be concluded that there are still areas in the developing DSE that can still be improved in terms of system computational time, redundancy and robustness of the system.
Volume: 8
Issue: 1
Page: 122-128
Publish at: 2017-10-01

Types of Circuit Breaker and its Application in Substation Protection

10.11591/ijeecs.v8.i1.pp213-220
Hui Hwang Goh , Sy yi Sim , Nur Iskandar bin Hamzah , Sulaiman bin Mazlan , Chin Wan Ling , Qing Shi Chua , Kai Chen Goh
Power system consists of the generation, transmission, distribution, and substation. All the power system component requires suitable protection devices as the protection system to protect the system during fault occur. In this paper, the circuit breaker has been selected as one of the protection devices in several applications. The types of circuit breaker that has been reviewed in this paper are oil circuit breaker (OCB), air circuit breaker (ACB), sulphur hexafluoride (SF6) circuit breaker, vacuum circuit breaker, and DC breaker which are hybrid DC breaker and solid-state DC breaker. Normally, the systems or the circuits disrupted or damaged by the fault. To implement the protection system in the system or circuit, the type of faults and cause of faults should be known to overcome the fault. To provide the suitable voltage for the consumer, the substation is needed to control the voltage transmitted at high voltage from the generating station. Protection system is also required in a substation.
Volume: 8
Issue: 1
Page: 213-220
Publish at: 2017-10-01

An Adaptive Scheme to Achieve Fine Grained Video Scaling

10.11591/ijeecs.v8.i1.pp43-58
S Safinaz , A. V. Ravi Kumar
A robust Adaptive Reconstruction Error Minimization Convolution Neural Network ( ARemCNN) architecture introduced to provide high reconstruction quality from low resolution using parallel configuration. Our proposed model can easily train the bulky datasets such as YUV21 and Videoset4.Our experimental results shows that our model outperforms many existing techniques in terms of PSNR, SSIM and reconstruction quality. The experimental results shows that our average PSNR result is 39.81 considering upscale-2, 35.56 for upscale-3 and 33.77 for upscale-4 for Videoset4 dataset which is very high in contrast to other existing techniques. Similarly, the experimental results shows that our average PSNR result is 38.71 considering upscale-2, 34.58 for upscale-3 and 33.047 for upscale-4 for YUV21 dataset.
Volume: 8
Issue: 1
Page: 43-58
Publish at: 2017-10-01

Extension Mode in Sliding Window Technique to Minimize Border Distortion Effect

10.11591/ijeecs.v8.i1.pp237-244
Saidatul Habsah Asman , Ahmad Farid Abidin , Nofri Yenita Dahlan
This paper deals with border distortion effect at starting and ending of finite signal by proposing sliding window technique and basic extension mode implementation. Single phase of transient and voltage sag is chosen to be analyzed in wavelet. The signal which being used for the analysis is simulated in Matlab 2017a. Disturbance signal decomposes into four level and Daubechies 4 (db4) has been chosen for computation. The proposed technique has been compared with conventional method which is finite length power disturbance analysis. Simulation result revealed that the proposed smooth-padding mode can be successfully minimized the border distortion effect compared to the zero-padding and symmetrization approach. 
Volume: 8
Issue: 1
Page: 237-244
Publish at: 2017-10-01

An Edge Exposure using Caliber Fuzzy C-means With Canny Algorithm

10.11591/ijeecs.v8.i1.pp59-68
Gowri Jeyaraman , Janakiraman Subbiah
Edge exposure or edge detection is an important and classical study of the medical field and computer vision.  Caliber Fuzzy C-means (CFCM) clustering Algorithm for edge detection depends on the selection of initial cluster center value. This endeavor to put in order a collection of pixels into a cluster, such that a pixel within the cluster must be more comparable to every other pixel. Using CFCM techniques first cluster the BSDS image, next the clustered image is given as an input to the basic canny edge detection algorithm. The application of new parameters with fewer operations for CFCM is fruitful. According to the calculation, a result acquired by using CFCM clustering function divides the image into four clusters in common. The proposed method is evidently robust into the modification of fuzzy c-means and canny algorithm. The convergence of this algorithm is very speedy compare to the entire edge detection algorithms. The consequences of this proposed algorithm make enhanced edge detection and better result than any other traditional image edge detection techniques.
Volume: 8
Issue: 1
Page: 59-68
Publish at: 2017-10-01

Smart Local Backup Protection for Smart Substation

10.11591/ijece.v7i5.pp2321-2328
M.N. Dazahra , F. Elmariami , A. Belfqih , J. Boukherouaa
This paper presents a novel smart local backup protection SLBP used for the support and backup of the protective relays in a smart substation. The proposed SLBP is based on the IEC61850 standards and the concept consists of the acquisition of Generic Object Oriented Substation Event GOOSE used for tripping and interlocks exchange between Intelligent Equipment Devices IEDs and the reading of the Sampled Value SV existing in the process bus coming from Mergin Units MU or Non-Conventional Instrument Transformers NCIT. Several logical schemes to protect different zones of the substation are presented and how can be integrated using data in the substation automation system. The SLBP was developed using an open source library and free operating system. Moreover, a low cost prototype is presented in order to evaluate the efficiency and the operation of the SLBP under diverse scenarios of the proposed logical protective schemes such us breaker failure and overcurrent protection
Volume: 7
Issue: 5
Page: 2321-2328
Publish at: 2017-10-01

Optimum Enhance Time of Use (ETOU) for Demand Side Electricity Pricing in Regulated Market: An Implementation Using Evolutionary Algorithm

10.11591/ijeecs.v8.i1.pp253-261
M. F. Sulaima , N. Y. Dahlan , Z.M. Yasin , N.A.M. Asari , Z.H. Bohari
The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are conventional method for C1 ETOU, C2 ETOU, and C1 ETOU with Optimization technique, and C2 ETOU with optimization technique tariff, respectively. The impact of the EP has been analysed, while the performance of six-time segmentation of C1 and C2 ETOU tariff indicate that the electricity cost for the medium voltage of installation has been reduced. It is hoped that the results from this study can benefit consumers by giving them the flexibility to rearrange their own energy consumption profile, so that the demand side will enjoy significant reduction of electricity cost in the future. 
Volume: 8
Issue: 1
Page: 253-261
Publish at: 2017-10-01

Transmission Line Fault Detection: A Review

10.11591/ijeecs.v8.i1.pp199-205
Hui Hwang Goh , Sy yi Sim , Asad Shaykh , Md. Humayun Kabir , Chin Wan Ling , Qing Shi Chua , Kai Chen Goh
Transmission line is the most important part of the power system.  Transmission lines a principal amount of power. The requirement of power and its allegiance has grown up exponentially over the modern era, and the major role of a transmission line is to transmit electric power from the source area to the distribution network. The exploded between limited production, and a tremendous claim has grown the focus on minimizing power losses. Losses like transmission loss and also conjecture factors as like as physical losses to various technical losses, Another thing is the primary factor it has a reactive power and voltage deviation are momentous in the long-range transmission power line. In essentially, fault analysis is a very focusing issue in power system engineering to clear fault in short time and re-establish power system as quickly as possible on very minimum interruption. However,  the fault detection that interrupts the transmission line is itself challenging task to investigate fault as well as improving the reliability of the system. The transmission line is susceptible given all parameters that connect the whole power system. This paper presents a review of transmission line fault detection.
Volume: 8
Issue: 1
Page: 199-205
Publish at: 2017-10-01

On-line Assessment of Voltage Stability using Synchrophasor Technology

10.11591/ijeecs.v8.i1.pp1-8
Satyendra Pratap Singh , S.P. Singh
Series of blackouts encountered in recent years in power system have been occurred because either of voltage or angle instability or both together was not detected within time and progressive voltage or angle instability further degraded the system condition, because of increase in loading. This paper presents the real-time assessment methodology of voltage stability using Phasor Measurement Unit (PMU) with observability of load buses only in power network. PMUs are placed at strategically obtained location such that minimum number of PMU’s can make all load buses observable. Data obtained by PMU’s are used for voltage stability assessment with the help of successive change in the angle of bus voltage with respect to incremental load, which is used as on-line voltage stability predictor (VSP). The real-time voltage phasors obtained by PMU’s are used as real time voltage stability indicator. The case study has been carried out on IEEE-14 bus system and IEEE-30 bus systems to demonstrate the results.
Volume: 8
Issue: 1
Page: 1-8
Publish at: 2017-10-01

A New Approach of Iris Detection and Recognition

10.11591/ijece.v7i5.pp2530-2536
Rubel Biswas , Jia Uddin , Md. Junayed Hasan
This paper proposes an IRIS recognition and detection model for measuring the e-security. This proposed model consists of the following blocks: segmentation and normalization, feature encoding and feature extraction, and classification. In first phase, histogram equalization and canny edge detection is used for object detection. And then, Hough Transformation is utilized for detecting the center of the pupil of an IRIS. In second phase, Daugmen’s Rubber Sheet model and Log Gabor filter is used for normalization and encoding and as a feature extraction method GNS (Global Neighborhood Structure) map is used, finally extracted feature of GNS is feed to the SVM (Support Vector Machine) for training and testing. For our tested dataset, experimental results demonstrate 92% accuracy in real portion and 86% accuracy in imaginary portion for both eyes. In addition, our proposed model outperforms than other two conventional methods exhibiting higher accuracy.
Volume: 7
Issue: 5
Page: 2530-2536
Publish at: 2017-10-01

Neoteric Hybrid Multilevel Cascade Inverter Based on Low Switch Numbers Along with Low Voltage Stress: Design, Analysis, Verification

10.11591/ijeecs.v8.i1.pp92-100
Rasool Esmailzadeh , A. Ajami , M.R. Banaei
Abstract: With the purpose of rein in the high voltage of flexible power systems, renovation and amendment of multi-level structures aimed at acquisition of high quality voltage is certainly required. In this regard, robust topology must be occupied that encompass the maximum output voltage levels along with minimum of switch number, of course, with taking into account of Peak Inverse Voltage (PIV). In this paper, a neoteric high-performance multilevel cascaded inverter is suggested up to the problem of repetitive output levels to be unraveled and also number of output voltage levels to be maximized. It has been constructed by series-connected multilevel inverters blocks and three-level inverter. The simulation results along with experimental results extracted by manufactured prototype have transparently approved high efficiency of proposed inverter as well as its feasibility. Apart from above, new mathematical approach has been presented to calculate and define the DC voltage sources magnitudes in asymmetric converter.
Volume: 8
Issue: 1
Page: 92-100
Publish at: 2017-10-01

Sizing Optimization of Large-Scale Grid-Connected Photovoltaic System Using Cuckoo Search

10.11591/ijeecs.v8.i1.pp169-176
Muhammad Zakyizzuddin Bin Rosselan , Shahril Irwan Sulaiman , Ismail Musirin
This study presents the development of Cuckoo Search (CS)-based sizing algorithm for sizing optimization of 5MW large-scale Grid-Connected Photovoltaic (GCPV) systems. CS was used to select the optimal combination of the system components which are PV module and inverter such that the Performance Ratio (PR) is correspondingly optimized. The oversized and undersized of this large-scale GCPV system can give huge impact towards the performanceof this system. Before incorporating the optimization methods, a sizing algorithm for large-scale GCPV systems was developed. Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods.The results showed that the CS-based sizing algorithm was unable to found the optimal PR for the system if compared with ISA. However, CS was outperformed ISA in producing the lowest computation time in finding the optimal sizing solution.
Volume: 8
Issue: 1
Page: 169-176
Publish at: 2017-10-01

The Application of Modified Least Trimmed Squares with Genetic Algorithms Method in Face Recognition

10.11591/ijeecs.v8.i1.pp154-158
Nur Azimah Abdul Rahim , Nor Azura Md. Ghani , Norazan Mohamed , Hishamuddin Hashim , Ismail Musirin
Severely occluded face images are the main problem in low performance of face recognition algorithms. In this paper, we apply a new algorithm, a modified version of the least trimmed squares (LTS) with a genetic algorithms introduce by [1]. We focused on the application of modified LTS with genetic algorithm method for face image recognition. This algorithm uses genetic algorithms to construct a basic subset rather than selecting the basic subset randomly. The modification in this method lessens the number of trials to obtain the minimum of the LTS objective function. This method was then applied to two benchmark datasets with clean and occluded query images. The performance of this method was measured by recognition rates. The AT&T dataset and Yale Dataset with different image pixel sizes were used to assess the method in performing face recognition. The query images were contaminated with salt and pepper noise. The modified LTS with GAs method is applied in face recognition framework by using the contaminated images as query image in the context of linear regression. By the end of this study, we can determine this either this method can perform well in dealing with occluded images or vice versa.
Volume: 8
Issue: 1
Page: 154-158
Publish at: 2017-10-01
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