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31,456 Article Results

Transient stability enhancement of statcom integration in power grid

10.11591/ijeecs.v16.i2.pp553-561
I. A Ethmane , A.K. Mahmoud , M. Maaroufi , A. Yahfdhou
To solve load growth of a hybrid existing electrical system, we at first build generation stations (wind, solar or thermical). And secondly in 2025 year, when the system is so meshed, some buses will be very far from production energy, the transits power will be lower than the transmission capacity, and the voltage drop out margin limit of stability. Therefore it is proposed to install Flexible AC Transmission System (FACTS) devices to enhance the transient power stability and quality in the power system. The power flow analysis of Newton Raphson method is performed on a seven (7) bus system with and without static synchronous compensator (STATCOM). The STATCOM is a shunt connected FACTS devices that are useful for reactive power compensation and mitigation of power quality problems in transmission and distribution systems. These investigations indicate the need of power flow analysis and determine best locations of STATCOM on the proposed system. The results of simulation have been programmed in MATLAB and PSS/E Simulator. In the end the expected disturbances and the power quality enhancement of the network in the horizon 2025 were attenuated by integration of STATCOM that is able to supply or absorb reactive power and to maintain the voltage at 1pu.
Volume: 16
Issue: 2
Page: 553-561
Publish at: 2019-11-01

Feedback-feedforward fuzzy logic approach for temperature control in bioethanol vacuum distiller

10.11591/ijeecs.v16.i2.pp678-684
Muhammad Aziz Muslim , Tegar Sukma Yudha , B.S.K.K. Ibrahim
Energy conservation and diversification are becoming a major research issue. Awareness of the limited sources of energy from fossil fuels encourages research on renewable energy. Bioethanol is a promising fuel substitute for gasoline. Bioethanol processing includes sugar extraction, fermentation, distillation, and absorption. Temperature and pressure controls are essential in bioethanol processing. This paper presents a feedback-feedforward fuzzy logic approach for temperature control in a bioethanol vacuum distiller. In this study, vacuum pressure is employed as feedforward inputs for a fuzzy logic controller. The feedforward input directly modifies the main controller, i.e., fuzzy logic controller, through fuzzy rules. The controller is implemented using Arduino Mega 2560 microcontroller. The results show that the proposed feedback-feedforward fuzzy logic controller could successfully maintain the temperature at the desired setpoint value with small steady-state error (3.85%) and relatively shorter settling time compared to classical PID controller and fuzzy logic controller.
Volume: 16
Issue: 2
Page: 678-684
Publish at: 2019-11-01

Improved newton-raphson with schur complement methods for load flow analysis

10.11591/ijeecs.v16.i2.pp699-605
Lea Tien Tay , William Ong Chew Fen , Lilik Jamilatul Awalin
The determination of power and voltage in the power load flow for the purpose of design and operation of the power system is very crucial in the assessment of actual or predicted generation and load conditions. The load flow studies are of the utmost importance and the analysis has been carried out by computer programming to obtain accurate results within a very short period through a simple and convenient way. In this paper, Newton-Raphson method which is the most common, widely-used and reliable algorithm of load flow analysis is further revised and modified to improve the speed and the simplicity of the algorithm. There are 4 Newton-Raphson algorithms carried out, namely Newton-Raphson, Newton-Raphson constant Jacobian, Newton-Raphson Schur Complement and Newton-Raphson Schur Complement constant Jacobian. All the methods are implemented on IEEE 14-, 30-, 57- and 118-bus system for comparative analysis using MATLAB programming. The simulation results are then compared for assessment using measurement parameter of computation time and convergence rate. Newton-Raphson Schur Complement constant Jacobian requires the shortest computational time.
Volume: 16
Issue: 2
Page: 699-605
Publish at: 2019-11-01

Projective synchronization for a cass of 6-D hyperchaotic lorenz system

10.11591/ijeecs.v16.i2.pp692-700
Ahmed S. Al-Obeidi , Saad Fawzi AL-Azzawi
This paper is concerned with the projective synchronization problem for a class of 6-D nonlinear dynamical system which is called hyperchaotic Lorenz system when the parameters of this system are unknown. Based on scaling factor  which belong to above strategy, four controller are proposed to achieve projective synchronization between two identical systems via using Lyapunov's direct method and nonlinear control strategy.  These scaling factor taken the values, and 2 for each control respectively. A numerical simulations are used to demonstrate the efficiency of the proposed controller.
Volume: 16
Issue: 2
Page: 692-700
Publish at: 2019-11-01

Short term load forecast of Kano zone using artificial intelligent techniques

10.11591/ijeecs.v16.i2.pp562-567
Huzaimu Lawal Imam , M.S Gaya , G. S. M Galadanci
Load forecast provides useful information for effective electricity dispatch, planning for future expansion and significantly enhances operational efficiency. Conventional techniques yield unsatisfactory forecast which results in high energy losses and in turn leads to high operational cost and suppressed electricity demand. This paper presents hybrid neuro fuzzy (HNF) and Nonlinear Auto-Regressive with eXogeneous input (NARX) neural network for the short term load prediction of Kano region Nigeria.  Simulation results obtained demonstrated the generalization capabilities of the models in predicting the load accurately well by achieving MAPE of 0.025% and 0.6551% for the HNF model and NARX network model respectively. The models could serve as promising tool for predicting Kano Zone load demand.
Volume: 16
Issue: 2
Page: 562-567
Publish at: 2019-11-01

PAPR analysis of OFDM system using AI based multiple signal representation methods

10.12928/telkomnika.v17i6.11511
Jyoti; Mewar University Shukla , Alok; Jaypee Institute of Information Technology Joshi , Rajesh; SRM University Tyagi
OFDM (orthogonal frequency division multiplexing) is widely used in 4th generation applications owing to its robustness in fading environments. The major issues with OFDM systems is the high PAPR (peak-to-average power ratio) of the transmitted signals, it leads to in and out of band distortion. SLM (selective mapping) and PTS (partial transmit sequence) are two key methods for PAPR reduction. Both the methods require exhaustive searching of phase factors to optimize the PAPR, these searches lead to high computational complexity. This paper discusses using optimization based PAPR reduction methods which an be used with PTS for the reduction of computational complexity and search space. In this paper we have analyzed PTS and SLM with particle swarm optimization (PSO), Artificial Bee Colony (ABC) and differential evolution (DE). PAPR and BER (bit error rate) comparison is done for both the cases.
Volume: 17
Issue: 6
Page: 2983-2991
Publish at: 2019-11-01

Simulative Study of Simple Ring Resonator Based Brewster Plate for Power System operation Stability

10.11591/ijeecs.v16.i2.pp1070-1076
Iraj Sadegh Amiri , Ahmed Nabih Zaki Rashed
This study has outlined the simulative study of simple ring resonator based Brewster plate in the air. The obtained results are achieved with the variations of space length, curvature radius and phase angle of the spherical mirror. Beam radius criterion and stability parameters are measured with the variations of refractive index and thickness of Brewster plate in the air. The negative and positive effects of increasing operating parameters are observed on the performance of ring resonator system efficiency. 
Volume: 16
Issue: 2
Page: 1070-1076
Publish at: 2019-11-01

Review on measurement techniques and technologies to propose new rating scale measurement for shariah compliant hotel industry in Malaysia

10.11591/ijeecs.v16.i2.pp685-691
Hazlin Fardila Abdul Hasim , NorHapiza Mohd Ariffin , Mohd Zaki Zakaria
The tourism industry based on the Islamic approach is increasingly accepted by the tourists.  This paper presents a review of measurement techniques and technologies’ scale measurement for Shariah Compliant Hotel Industry in Malaysia. Since the use of the rating system in Syariah Hotel Industry in Malaysia has yet to be implemented, it is difficult for the industry to determine the status level of a hotel. Furthermore, the consumers are unable to make the right choice based on their own needs. This study aims to propose new Rating Assessment for Scale Measurement system focusing on hotel industry based on Shariah Compliant standard known as Shariah Compliant Hotel Rating Measurement Scale System (SCHRMS). Scale measurement will be used to ensure all the Shariah Compliant Certificates are certified with certain level and follow the same standard. Multiple characteristics and categories must be clarified or considered when processing rating assessment for Shariah Compliance (SC) hotel. To solve the multiple characteristics’ issues, Fuzzy Analytic Hierarchy Process will be used. The process is accurate and suitable for selecting various types of information and can be used as a decision-making tool because it controls uncertain and inaccurate data. The raw data obtained from questionnaires as well as structured and unstructured interview will be analyzed using Rasch Analysis Method. Only this method is will be able to comply to the five main principles of analysis for a more meaningful and accurate conclusion of the research data obtained. Through this system that will developed, the problem related to rating measurement for SC hotel will be solved. The SC hotel rating system will be parallel to the conventional based hotel. The system is accepted for the convenience of Muslims as well as non-Muslims globally.
Volume: 16
Issue: 2
Page: 685-691
Publish at: 2019-11-01

Chaotic immune symbiotic organisms search for SVC installation in voltage security control

10.11591/ijeecs.v16.i2.pp623-630
Mohamad Khairuzzaman Mohamad Zamani , Ismail Musirin , Saiful Izwan Suliman , Muhammad Murtadha Othman
Parallel with the urbanization of the world, energy demand in the world also increased. The increase in energy demand will require a power system to be operated near its stability limit. To mitigate the problem, Flexible Alternating Current Transmission System (FACTS) devices can be installed as a compensation scheme to improve voltage security in a power system. For an effective compensation, FACTS devices should be optimally allocated in a power system. Although optimization techniques can be implemented to optimally allocate these devices, problems have been reported which would affect the performance of the optimization techniques in terms of producing high quality solutions. This paper presents the implementation of Chaotic Immune Symbiotic Organisms Search for solving optimal Static VAr Compensator (SVC) allocation problem for voltage security control. The optimization is validated in IEEE 26-Bus Reliability Test System (RTS) realizes the capability of CISOS in solving the optimization problem. Comparative studies with respect to Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) resulting in good agreement on the results and demonstrated superior performance of CISOS. Results of the study can be beneficial to power system community in terms of compensation planning prior to real world implementation.
Volume: 16
Issue: 2
Page: 623-630
Publish at: 2019-11-01

Artificial neural network and partial least square in predicting blood hemoglobin using near-infrared spectrum

10.11591/ijeecs.v16.i2.pp701-708
Mohd Nazrul Effendy Mohd Idrus , Kim Seng Chia
Predictive models is crucial in near-infrared (NIR) spectroscopic analysis. Partial least square - artificial neural network (PLS-ANN) is a hybrid method that may improve the performance of prediction in NIR spectroscopic analysis. This study investigates the advantage of PLS-ANN over the well-known modelling in spectroscopy analysis that is partial least square (PLS) and artificial neural network (ANN). The results show that ANN that coupled with first order SG derivatives achieved the best prediction with root mean square error of prediction (RMSEP) of 0.3517 gd/L and coefficient of determination ( ) of 0.9849 followed by PLS-ANN with RMSEP of 0.4368 gd/L and  of 0.9787, and PLS with RMSEP of 0.4669 gd/L and  of 0.9727. This suggests that the spectrum information may unable to be totally represented by the first few latent variables of PLS and a nonlinear model is crucial to model these nonlinear information in NIR spectroscopic analysis.
Volume: 16
Issue: 2
Page: 701-708
Publish at: 2019-11-01

An adaptive gravitational search algorithm for global optimization

10.11591/ijeecs.v16.i2.pp724-729
Ying-Ying Koay , Jian-Ding Tan , Chin-Wai Lim , Siaw-Paw Koh , Sieh-Kiong Tiong , Kharudin Ali
Optimization algorithm has become one of the most studied branches in the fields of artificial intelligent and soft computing. Many powerful optimization algorithms with global search ability can be found in the literature. Gravitational Search Algorithm (GSA) is one of the relatively new population-based optimization algorithms. In this research, an Adaptive Gravitational Search Algorithm (AGSA) is proposed. The AGSA is enhanced with an adaptive search step local search mechanism. The adaptive search step begins the search with relatively larger step size, and automatically fine-tunes the step size as iterations go. This enhancement grants the algorithm a more powerful exploitation ability, which in turn grants solutions with higher accuracies. The proposed AGSA was tested in a test suit with several well-established optimization test functions. The results showed that the proposed AGSA out-performed other algorithms such as conventional GSA and Genetic Algorithm in the benchmarking of speed and accuracy. It can thus be concluded that the proposed AGSA performs well in solving local and global optimization problems. Applications of the AGSA to solve practical engineering optimization problems can be considered in the future.
Volume: 16
Issue: 2
Page: 724-729
Publish at: 2019-11-01

A secure group based authentication protocol for machine to machine communications in LTE-WLAN interworking architecture

10.11591/ijeecs.v16.i2.pp848-859
Mariya Ouaissa , Abdallah Rhattoy
Machine to Machine (M2M) communication has been used in applications such as telemetry, industry, automation and health. Support for a large number of devices has been considered an essential requirement in M2M communications. During this time, security is the most important challenge; M2M cannot access secure networks through effective authentication, all relevant M2M applications cannot be accepted. The challenge of M2M research is authentication by the group when a large number of M2M devices simultaneously accessing the network will cause severe authentication signaling congestion. The group based model under an M2M architecture, especially when the Machine Type Communication (MTC) devices belong to the non 3rd Generation Partnership Project (3GPP) network, will face a new challenge of access authentication. In this paper, we propose a group based authentication and key agreement protocol for machine type communications combining Elliptic Curve based Diffie-Hellman (ECDH) on the Extensible Authentication Protocol (EAP). Compared to EAP-AKA and other existing authentication protocols, our solution provides increased security against various malicious activities and better performance in terms of signaling overhead, bandwidth consumption and transmission cost.
Volume: 16
Issue: 2
Page: 848-859
Publish at: 2019-11-01

Detection of fault during power swing in test system interconnected with DG

10.11591/ijeecs.v16.i2.pp577-585
Nor Zulaily Mohamad , Ahmad Farid Abidin , Ismail Musirin
Distance relay is prone to mal-operate during power swing, thus most of modern distance relay design is equipped with power swing blocking scheme to block the operation during power swing and reset the blocking operation whenever a fault occurs during power swing. However, the detection of fault during power swing especially for high resistance fault possess a challenging task, therefore it may cause the unblocking function to vulnerable to operate. This paper presents the development of a detection scheme for detecting fault during power swing in test system interconnected with Distributed Generation (DG). In this study, the detection scheme is proposed based on S-Transform analysis on the distance relay input voltage signal. It is demonstrated that the proposed S-Transform detection based scheme can effectively detect various type of fault during power swing includes high resistance fault, as well as able to operate correctly even with the presence of DG in the test system.
Volume: 16
Issue: 2
Page: 577-585
Publish at: 2019-11-01

Analytics of stock market prices based on machine learning algorithms

10.11591/ijeecs.v16.i2.pp1050-1058
Puteri Hasya Damia Abd Samad , Sofianita Mutalib , Shuzlina Abdul-Rahman
This study focuses on the use of machine learning algorithms to analyse financial news on stock market prices. Stock market prediction is a challenging task because the market is known to be very volatile and dynamic. Investors face these kinds of problems as they do not properly understand which stock product to subscribe or when to sell the product with an optimum profit. Analyzing the information individually or manually is a tedious task as many aspects have to be considered. Five different companies from Bursa Malaysia namely CIMB, Sime Darby, Axiata, Maybank and Petronas were chosen in this study. Two sets of experiments were performed based on different data types. The first experiment employs textual data involving 6368 articles, extracted from financial news that have been classified into positive or negative using Support Vector Machine (SVM) algorithm. Bags of words and bags of combination words are extracted as the features for the first experiment. The second experiment employs the numeric data type extracted from historical data involving 5321 records to predict whether the stock price is going up (positive) or down (negative) using Random Forest algorithm. The Rain Forest algorithm gives better accuracy in comparison with SVM algorithm with 99% and 68% accuracy respectively. The results demonstrate the complexities of the textual-based data and demand better feature extraction technique.
Volume: 16
Issue: 2
Page: 1050-1058
Publish at: 2019-11-01

Numerical computation for solving fuzzy differential equations

10.11591/ijeecs.v16.i2.pp1026-1033
Fuziyah Ishak , Najihah Chaini
Fuzzy differential equations (FDEs) play important roles in modeling dynamic systems in science, economics and engineering. The modeling roles are important because most problems in nature are indistinct and uncertain. Numerical methods are needed to solve FDEs since it is difficult to obtain exact solutions. Many approaches have been studied and explored by previous researchers to solve FDEs numerically. Most FDEs are solved by adapting numerical solutions of ordinary differential equations. In this study, we propose the extended Trapezoidal method to solve first order initial value problems of FDEs. The computed results are compared to that of Euler and Trapezoidal methods in terms of errors in order to test the accuracy and validity of the proposed method. The results shown that the extended Trapezoidal method is more accurate in terms of absolute error. Since the extended Trapezoidal method has shown to be an efficient method to solve FDEs, this brings an idea for future researchers to explore and improve the existing numerical methods for solving more general FDEs.
Volume: 16
Issue: 2
Page: 1026-1033
Publish at: 2019-11-01
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