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29,922 Article Results

Comparative study of the price penalty factors approaches for Bi-objective dispatch problem via PSO

10.11591/ijece.v10i4.pp3343-3349
Mohammed Amine Meziane , Youssef Mouloudi , Abdelghani Draoui
One of the main objectives of electricity dispatch centers is to schedule the operation of available generating units to meet the required load demand at minimum operating cost with minimum emission level caused by fossil-based power plants. Finding the right balance between the fuel cost the green gasemissionsis reffered as Combined Economic and Emission Dispatch (CEED) problem which is one of the important optimization problems related the operationmodern power systems. The Particle Swarm Optimization algorithm (PSO) is a stochastic optimization technique which is inspired from the social learning of birds or fishes. It is exploited to solve CEED problem. This paper examines the impact of six penalty factors like "Min-Max", "Max-Max", "Min-Min", "Max-Min", "Average" and "Common" price penalty factors for solving CEED problem. The Price Penalty Factor for the CEED is the ratio of fuel cost to emission value. This bi-objective dispatch problem is investigated in the Real West Algeria power network consisting of 22 buses with 7 generators. Results prove capability of PSO in solving CEED problem with various penalty factors and it proves that Min-Max price penalty factor provides the best compromise solution in comparison to the other penalty factors.
Volume: 10
Issue: 4
Page: 3343-3349
Publish at: 2020-08-01

Medium term load demand forecast of Kano zone using neural network algorithms

10.12928/telkomnika.v18i4.14032
Huzaimu Lawal; Bayero University Kano Imam , Muhammad Sani; Kano University of Science and Technology Gaya , G. S. M.; Bayero University Kano Galadanci
Electricity load forecasting refers to projection of future load requirements of an area or region or country through appropriate use of historical load data. One of several challenges faced by the Nigerian power distribution sectors is the overloaded power distribution network which leads to poor voltage distribution and frequent power outages. Accurate load demand forecasting is a key in addressing this challenge. This paper presents a comparison of generalized regression neural network (GRNN), feed-forward neural network (FFNN) and radial basis function neural network for medium term load demand estimation. Experimental data from Kano electricity distribution company (KEDCO) were used in validating the models. The simulation results indicated that the neural network models yielded promising results having achieved a mean absolute percentage error (MAPE) of less than 10% in all the considered scenarios. The generalization capability of FFNN is slightly better than that of RBFNN and GRNN model. The models could serve as a valuable and promising tool for the forecasting of the load demand.
Volume: 18
Issue: 4
Page: 2112-2117
Publish at: 2020-08-01

Enhancement of power quality using microprocessor based shunt active power filter for unbalanced load

10.11591/ijece.v10i4.pp3393-3402
Madhu B. R. , Dinesh M. N. , Tsewang Thinlas , Deril Menezes
Power quality is the most significant factor of power sector. The end user equipment such as induction motor, inverters, rectifiers inject harmonics into power system that influences the quality of power delivered. The presence of harmonics forces the use of instantaneous reactive power theory to calculate instantaneous power that helps in finding the compensating currents to eliminate harmonics. The control action required by active filter is accomplished by STM32F303RET6 microcontroller. Single phase induction motor is used as a dynamic nonlinear load in one of the three phases and resistive loads on the other two phases. TRIAC based RC triggering circuit was used to control the single phase induction motor. This paper presents the simulation and hardware implementation of shunt active power filter for 3 phase 4 wire unbalanced system. The hardware results show that THD in the source side has been reduced from 50.7% to 9.6% by implementing the SAPF.
Volume: 10
Issue: 4
Page: 3393-3402
Publish at: 2020-08-01

A probabilistic multi-objective approach for FACTS devices allocation with different levels of wind penetration under uncertainties and load correlation

10.11591/ijece.v10i4.pp3898-3910
M. EL-Azab , W. A. Omran , S. F. Mekhamer , H. E. A. Talaat
This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the Multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30-bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
Volume: 10
Issue: 4
Page: 3898-3910
Publish at: 2020-08-01

The maximum power point tracking based-control system for small-scale wind turbine using fuzzy logic

10.11591/ijece.v10i4.pp3927-3935
Quang-Vi Ngo , Chai Yi , Trong-Thang Nguyen
This paper presents the research on small-scale wind turbine systems based on the Maximum Power Point Tracking (MPPT) algorithm. Then propose a new structure of a small-scale wind turbine system to simplify the structure of the system, making the system highly practical. This paper also presented an MPPT-Fuzzy controller design and proposed a control system using the wind speed sensor for small-scale wind turbines. Systems are simulated using Matlab/Simulink software to evaluate the feasibility of the proposed controller. As a result, the system with the MPPT-Fuzzy controller has much better quality than the traditional control system.
Volume: 10
Issue: 4
Page: 3927-3935
Publish at: 2020-08-01

The role of parent-child relationship, school climate, happiness, and empathy to predict cyberbullying behavior

10.11591/ijere.v9i3.20299
Triantoro Safaria , Hadi Suyono
The lack of research on cyberbullying among Indonesian adolescents has become one of the critical arguments of this research. This study aimed to discover the factors that contribute to cyberbullying. This study took samples of students from three schools. The sample was 112 junior to senior high school students. The findings of this study indicate that school climate, parent-child relationship, and empathy have a significant role that encourages cyberbullying.
Volume: 9
Issue: 3
Page: 548-557
Publish at: 2020-08-01

Optimal cost allocation algorithm of transmission losses to bilateral contracts

10.12928/telkomnika.v18i4.14226
Conny K.; Politeknik Negeri Bandung Wachjoe , Hermagasantos; Politeknik Negeri Bandung Zein , Fitria; Politeknik Negeri Bandung Yulistiani
One of the trends in electricity reform is the involvement of bilateral contracts that will participate in electricity business development. Bilateral agreements require fair transmission loss costs compared with the integrated power system. This paper proposes a new algorithm in determining the optimal allocation of transmission loss costs for bilateral contracts based on the direct method in economic load dispatch. The calculation for an optimal power flow applies fast decoupled methods. At the same time, the determination of a fair allocation of transmission losses uses the decomposition method. The simulation results of the optimal allocation of power flow provide comparable results with previous studies. This method produces a fair allocation of optimal transmission loss costs for both integrated and bilateral parties. The proportion allocation of the transmission lines loss incurred by the integrated system and bilateral contracts reflects a fair allocation of R. 852.589 and R. 805.193, respectively.
Volume: 18
Issue: 4
Page: 2132-2139
Publish at: 2020-08-01

Voronoi diagram with fuzzy number and sensor data in an indoor navigation for emergency situation

10.12928/telkomnika.v18i4.14905
Nanna; Universiti Teknikal Malaysia Melaka Suryana , Fandy Setyo; Universiti Teknikal Malaysia Melaka Utomo , Mohd Fairuz Iskandar; Universiti Teknikal Malaysia Melaka Othman , Mohd Nazrin; Universiti Teknikal Malaysia Melaka Muhammad
Finding shortest and safest path during emergency situation is critical. In this paper, an indoor navigation during an emergency time is investigated using the combination of Voronoi Diagram and fuzzy number. The challenge in indoor navigation is to analyses the network when the shortest path algorithm does not work as always expected. There are some existing methods to generate the network model. First, this paper will discuss the feasibility and accuracy of each method when it is implemented on building environment. Next, this paper will discuss selected algorithms that determine the selection of the best route during an emergency situation. The algorithm has to make sure that the selected route is the shortest and the safest route to the destination. During a disaster, there are many uncertainties to deal with in determining the shortest and safest route. Fuzzy logic can be hardly called for to deal with these uncertainties. Based on sensor data, this paper will also discuss how to solve shortest path problem using a fuzzy number.
Volume: 18
Issue: 4
Page: 1990-1997
Publish at: 2020-08-01

Suicidal thoughts among university students: The role of mattering, state self-esteem and depression level

10.11591/ijere.v9i3.20587
Kususanto Ditto Prihadi , Charon Y.S. Wong , Erina Y.V. Chong , Kate Y.X. Chong
The protective role of mattering on suicide ideation among university students was examined. Our study is grounded in the Interpersonal-Psychological Theory of Suicide, which led to a hypothesis that between depression levels and state self-esteem has significant serial multiple mediating effects on the relationship between mattering and suicide ideation. University students from various nationality who study in Indonesia and Malaysia (n=509) responded to General Mattering Scale, State Self-Esteem Scale, Beck’s Depression Inventory, and Suicide Ideation Attributes Scale, as well as demographic details including their gender, spirituality, education, birth order and nationality. The result of Bootstrap analyses with 95% confident interval from 5000 samples suggested that the serial mediation partially occurred to the link between mattering and suicide ideation.
Volume: 9
Issue: 3
Page: 494-502
Publish at: 2020-08-01

Design and modeling of solenoid inductor integrated with FeNiCo in high frequency

10.12928/telkomnika.v18i4.12139
Abdelhadi; Ahmed Zabana University Centre Namoune , Rachid; Hassiba Benbouali University Taleb , Noureddine; Hassiba Benbouali University Mansour
In this work, the design and modeling of the solenoid inductor are discussed. The layout of integrated inductors with magnetic cores and their geometrical parameters are developed. The quality factor Q and inductance value L are extracted from the S-parameters and plotted versus frequency. The effect of solenoid inductor geometry on inductance and quality factor are studied via simulation using MATLAB. The solenoid inductor geometry parameters considered are the number of turns, length of the magnetic core, the width of a magnetic core, the gap between turns, the thickness of the magnetic core, the thickness of the coil and oxide thickness of solenoid inductor. The performance of the proposed solenoid inductor integrated with FeNiCo is compared with other solenoid inductors.
Volume: 18
Issue: 4
Page: 1746-1753
Publish at: 2020-08-01

∈φ-contraction and some fixed point results via modified ω-distance mappings in the frame of complete quasi metric spaces and applications

10.11591/ijece.v10i4.pp3839-3853
Kamaleldin Abodayeh , T. Qawasmeh , W. Shatanawi , A. Tallafha
In this Article, we introduce the notion of an ∈φ-contraction which based on modified ω-distance mappings and employ this new definition to prove some fixed point result. Moreover, we introduced an interesting example and an application to highlight the importance of our work.
Volume: 10
Issue: 4
Page: 3839-3853
Publish at: 2020-08-01

Early detection of breast cancer using mammography images and software engineering process

10.12928/telkomnika.v18i4.14718
Muayad Sadik; University of Technology-Iraq Croock , Saja Dhyaa; University of Technology-Iraq Khuder , Ayad Esho; University of Technology-Iraq Korial , Sahar Salman; University of Technology-Iraq Mahmood
The breast cancer has affected a wide region of women as a particular case. Therefore, different researchers have focused on the early detection of this disease to overcome it in efficient way. In this paper, an early breast cancer detection system has been proposed based on mammography images. The proposed system adopts deep-learning technique to increase the accuracy of detection. The convolutional neural network (CNN) model is considered for preparing the datasets of training and test. It is important to note that the software engineering process model has been adopted in constructing the proposed algorithm. This is to increase the reliably, flexibility and extendibility of the system. The user interfaces of the system are designed as a website used at country side general purpose (GP) health centers for early detection to the disease under lacking in specialist medical staff. The obtained results show the efficiency of the proposed system in terms of accuracy up to more than 90% and decrease the efforts of medical staff as well as helping the patients. As a conclusion, the proposed system can help patients by early detecting the breast cancer at far places from hospital and referring them to nearest specialist center.
Volume: 18
Issue: 4
Page: 1784-1794
Publish at: 2020-08-01

A progressive domain expansion method for solving optimal control problem

10.12928/telkomnika.v18i4.15047
Olalekan; Kwara State University Ogunbiyi , Oludare Y.; Federal University of Petroleum Resources Ogundepo , Madugu I.; Kano State University of Science and Technology Wudi Sani , Cornelius; Achievers University Thomas , Benjamin J.; University of Ilorin Olufeagba
Electricity generation at the hydropower stations in Nigeria has been below the expected value. While the hydro stations have a capacity to generate up to 2,380 MW, the daily average energy generated in 2017 was estimated at around 846 MW. A factor responsible for this is the lack of a proper control system to manage the transfer of resources between the cascaded Kainji-Jebba Hydropower stations operating in tandem. This paper addressed the optimal regulation of the operating head of the Jebba hydropower reservoir in the presence of system constraints, flow requirement and environmental factors that are weather-related. The resulting two-point boundary value problem was solved using the progressive expansion of domain technique as against the shooting or multiple shooting techniques. The results provide the optimal inflow required to keep the operating head of the Jebba reservoir at a nominal level, hence ensuring that the maximum number of turbo-alternator units are operated.
Volume: 18
Issue: 4
Page: 2062-2069
Publish at: 2020-08-01

Machine learning based lightweight interference mitigation scheme for wireless sensor network

10.12928/telkomnika.v18i4.14879
Ali; Universiti Teknologi Malaysia Suzain , Rozeha A.; Universiti Teknologi Malaysia Rashid , M. A.; Universiti Teknologi Malaysia Sarijari , A. Shahidan; Universiti Teknologi Malaysia Abdullah , Omar A.; Universiti Teknologi Malaysia Aziz
The interference issue is most vibrant on low-powered networks like wireless sensor network (WSN). In some cases, the heavy interference on WSN from different technologies and devices result in life threatening situations. In this paper, a machine learning (ML) based lightweight interference mitigation scheme for WSN is proposed. The scheme detects and identifies heterogeneous interference like Wifi, bluetooth and microwave oven using a lightweight feature extraction method and ML lightweight decision tree. It also provides WSN an adaptive interference mitigation solution by helping to choose packet scheduling, Acknowledgement (ACK)-retransmission or channel switching as the best countermeasure. The scheme is simulated with test data to evaluate the accuracy performance and the memory consumption. Evaluation of the proposed scheme’s memory profile shows a 14% memory saving compared to a fast fourier transform (FFT) based periodicity estimation technique and 3% less memory compared to logistic regression-based ML model, hence proving the scheme is lightweight. The validation test shows the scheme has a high accuracy at 95.24%. It shows a precision of 100% in detecting WiFi and microwave oven interference while a 90% precision in detecting bluetooth interference.
Volume: 18
Issue: 4
Page: 1762-1770
Publish at: 2020-08-01

The role of entrepreneurial intention in predicting vocational high school students’ employability

10.11591/ijere.v9i3.20580
Fatwa Tentama , Sabrina Yusantri
One of the factors that contribute to the level of employability is entrepreneurial intention. This study discusses the role of entrepreneurial intentions on students' employability. The population in this study was all students of grade XII of Vocational High School Koperasi Yogyakarta, Indonesia, consisting of 141 students. The sample in this study was 86 students. The sample selection was done by randomizing using a cluster random sampling technique. Methods of data collection used in this study are scales, employability scale, and entrepreneurial intentions scale. Analysis of the data used in this study is the product-moment analysis technique. The results of data analysis showed the correlation between entrepreneurial intentions and employability where r = 0.339 with p = 0.001 (p < 0.01), which showed a very significant positive correlation between the two variables at the research site. It means that the level of employability can be predicted based on entrepreneurial intention. The entrepreneurial intention contributed 11.5% to employability, and the remaining 88.5% can be influenced by other variables.
Volume: 9
Issue: 3
Page: 558-563
Publish at: 2020-08-01
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