IJITEE (International Journal of Information Technology and Electrical Engineering)
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Ant Colony Optimization for Resolving Unit Commitment Issues by Considering Reliability Constraints
Full text linkUnit Commitment or generator scheduling is one of complex combination issues aiming to obtain the cheapest generating power total costs. Ant Colony Optimization is proposed as a method to solve Unit Commitment issues because it has a better result convergence according to one of journals that reviews methods to solve Unit Commitment issues. Ant Colony Optimization modification into Nodal Ant Colony Optimization as well as addition of several elements are also conducted to overcome Ant Colony Optimization limitations in resolving Unit Commitment issues. Nodal Ant Colony Optimization simulations are then compared with Genetic Algorithm and Simulated Annealing methods which previously has similar simulations. Reliability index combination in a form of Loss of Load Probability and Expected Unserved Energy are also added as reliability constraints in the system. Comparison of three methods shows that Nodal Ant Colony Optimization is able to provide better results up to 0.08% cheaper than Genetic Algorithm or Simulated Annealing methods
Fault Location Algorithm for HVDC Transmission Based on Synchronized Fault Time
Full text linkTo determine the fault location of the dc line fault in an HVDC transmission system, a new algorithm based on the traveling wave method and learning based method is proposed in this paper. The relationship between the traveling wave time of arrival differences with fault location is presented. The differences in traveling wave time of arrival measured at both ends of transmission line combined with associated fault locations form a fault pattern which is used to perform a simple calculation in order to determine the disturbance location. The fault current for different fault locations is simulated using the electromagnetic transient simulation software EMTDC/PSCAD. Performance of the proposed fault location algorithm is investigated using various fault location and resistance. The impact of data sampling rate also being investigated here. The simulation result shows that the proposed algorithm can reduce the sampling frequency and the number of train feature with the same accuracy
Testing of Several Paper Types as Insulators for Electric Power Systems
Full text linkAbstract— This research was based on high voltage equipment failure due to an increase in temperature and humidity on insulating materials. This can cause the power system reliability to decrease. On the other hand, paper is frequently found and used in everyday life. Paper can be categorized as a solid insulator even tough its use in the electric power system can be considered as minimum. This paper aimed to determine electrical insulation characteristics of three types of paper on market and to determine the amount of failed voltage and leakage current of test materials included with other factors such as temperature rise effect as well as humidity conditions in sample testing. The employed test samples were photo paper, duplex paper, and samson craft paper with a length of 7 cm and width of 7 cm with different thickness for each paper type. Tests were carried out with two paper conditions, i.e. paper was soaked in Shell Diala B oil and was not soaked in Shell Diala B oil, so that the significance of the oil on the paper used as an ingredient in testing could be known. The test results showed that temperature and humidity affected dielectric strength magnitude and test sample leakage current value. In addition, it was also found that test sample result impregnated with Shell Diala B had a higher dielectric magnitude compared to the unimpregnated test sample. Test samples impregnated with Shell Diala B oil had a leakage current value which tended to be smaller than the unimpregnated test sample
Relational into Non-Relational Database Migration with Multiple-Nested Schema Methods on Academic Data
Full text linkThe rapid development of internet technology has increased the need of data storage and processing technology application. One application is to manage academic data records at educational institutions. Along with massive growth of information, decrement in the traditional database performance is inevitable. Hence, there are many companies choose to migrate to NoSQL, a technology that is able to overcome the traditional database shortcomings. However, the existing SQL to NoSQL migration tools have not been able to represent SQL data relations in NoSQL without limiting query performance. In this paper, a relational database transformation system transforming MySQL into non-relational database MongoDB was developed, using the Multiple Nested Schema method for academic databases. The development began with a transformation scheme design. The transformation scheme was then implemented in the migration process, using PDI/Kettle. The testing was carried out on three aspects, namely query response time, data integrity, and storage requirements. The test results showed that the developed system successfully represented the relationship of SQL data in NoSQL, provided complex query performance 13.32 times faster in the migration database, basic query performance involving SQL transaction tables 28.6 times faster on migration results, and basic performance Queries without involving SQL transaction tables were 3.91 times faster in the migration source. This shows that the theory of the Multiple Nested Schema method, aiming to overcome the poor performance of queries involving many JOIN operations, is proved. In addition, the system is also proven to be able to maintain data integrity in all tested queries. The space performance test results indicated that the migrated database transformed using the Multiple Nested Schema method showed a storage requirement of 10.53 times larger than the migration source database. This is due to the large amount of data redundancy resulting from the transformation process. However, at present, storage performance is not a top priority in data processing technology, so large storage requirements are a consequence of obtaining efficient query performance, which is still considered as the first priority in data processing technology
Real-Time Indonesian Language Speech Recognition with MFCC Algorithms and Python-Based SVM
Full text linkAbstract — Automatic Speech Recognition (ASR) is a technology that uses machines to process and recognize human voice. One way to increase recognition rate is to use a model of language you want to recognize. In this paper, a speech recognition application is introduced to recognize words "atas" (up), "bawah" (down), "kanan" (right), and "kiri" (left). This research used 400 samples of speech data, 75 samples from each word for training data and 25 samples for each word for test data. This speech recognition system was designed using Mel Frequency Cepstral Coefficient (MFCC) as many as 13 coefficients as features and Support Vector Machine (SVM) as identifiers. The system was tested with linear kernels and RBF, various cost values, and three sample sizes (n = 25, 75, 50). The best average accuracy value was obtained from SVM using linear kernels, a cost value of 100 and a data set consisted of 75 samples from each class. During the training phase, the system showed a f1-score (trade-off value between precision and recall) of 80% for the word "atas", 86% for the word "bawah", 81% for the word "kanan", and 100% for the word "kiri". Whereas by using 25 new samples per class for system testing phase, the f1-score was 76% for the "atas" class, 54% for the "bawah" class, 44% for the "kanan" class, and 100% for the "kiri" class
Design of Electronic Mass Balance of Gram Scale Using a Gage Strain Sensor
Full text linkThis research is conducted by utilizing strain gage uniaxial sensor with internal resistance 120 ohms and brass cantilever beam that is to build electronic mass scale in gram level. Basically, the aim of this research is to study deflect phenomenon measured by the strain gage sensor attached in the end of brass cantilever beam. Brass material was chosen to build cantilever as its Young moudulus contanst is bigger than other materials. Whilst mass loads for analizing brass cantilever profile are calibrated by manual Ohaus mass scale (PA214 type) with 0.07 gram load variations. The test result of this electronic mass scale system gets relationship of mass load data variation versus output voltage data (from differential amplifier). The relationship between mass and voltage can be approached by polynomial formula m = 4.2372V2 – 2.4551V + 1.5606 where m in gram and V in volt, and it gets 0.07 or 7% average error (less than linear formula approach). This formula is used further for programming ADC in 8-bit microcontroller to calculate mass and the calculation is shown in LCD 16x2
Determination of MS Location through Building Using AoA Method of Frequency 47 GHz
Full text linkThis research discusses the determination of mobile station (MS) location of the uplink communication system. The location determination mobile station is based on the angle-of-arrival (AoA) method. The communication propagation is influenced by building environment. The building environment was modeled with diffraction method. Several diffraction methods were used such as single knife edge, and multiple knife edge method. The communication frequency used was 47 GHz. The analysis used percentage value at coverage area and comparison of error percent values between two method to determine mobile station location. The percentage of the communication coverage area obtained was 71.4% or of 255 from 300 nodes. The comparison methods used for mobile station location determination were the selection of the best SNR and localization technique. The error percentage value based on the selection of the best SNR method is 0.95%. The error percentage value based on localization technique method is 0.78%
Forecasting Analysis on Land Detection System Based on Geographic Information System
Full text linkGeographic Information System (GIS) is an information system that performs geographic-based data visualization. The system performs mapping between various data points based on geographical location. Difficulties in mapping land in a region is the basis for the development of GIS applications for the detection of land. This system does not only detect vacant land in a region, but it also provides identification of land, and provides information about the size of the land, the land position, as well as access to nearby public facilities. The system is developed using a mobile platform as a value system that is more flexible and dynamic. For the analysis of the forecasting in an area uses a multiple regression method involving three independent variables, namely the use of dry land, the use of building land and land use. The results of the predictive forecasting provides location points of interest and public facilities located in the location which make it easy to give consideration in selecting a location which is appropriate to build
Parameter Identification of Nonlinear System on Combustion Engine Based MVEM using PEM
Full text linkIn four-stroke engine injection system, often called spark ignition (SI) engine, the air-fuel ratio (AFR) is taken from the measurement of lambda sensor in the exhaust. This sensor does not directly describe how much AFR in the combustion chamber due to the large transport delay. Therefore, the lambda sensor is used only as a feedback in AFR control "correction", not as the "main" control. The purpose of this research is to identify the parameters of the non-linear system in SI engines to produce AFR estimator. The AFR estimator is expected to be used as a feedback of the main "AFR" control system. The process of identifying the parameters using the Gauss-Newton method, due to its rapid computation to Achieve convergence, is based on prediction error minimization (PEM). The models of AFR estimator is an open-loop system without a universal exhaust gas oxygen (UEGO) sensors as feedback, called a virtual AFR sensor. The high price of UEGO sensors makes the virtual AFR sensor can be a practical solution to be applied in AFR control. The model in this research is based on the mean value engine models (MVEM) with some modifications. The research dataset was taken from a Hyundai Verna 2002 with the additional UEGO type of lambda sensors. The throttle opening angle (input) is played by stepping on the gas pedal and the signal to the injector (input) is set to a certain quantity to produce the AFR (output) value read by the UEGO sensor. This research produces an open loop estimator model or AFR virtual sensors with normalized root mean square error (NRMSE) = 0.06831 = 6.831%
Operation Region Selector Circuit to Obtain Maximum Efficiency of 250 W Boost Converter
Full text linkInterleaved boost converter gives good conversion efficiency due to its zero-current switching capability when operating in discontinuous conduction mode while keeping its input-output ripple current low. However, operating this kind of converter at interleaved operation for all the time gives poor efficiency under light-load condition. In this paper, an automatic operation region selector switch based on detection of the continuous or discontinuous current mode is proposed. With this switch, during the light-load condition, only one converter is activated, while during full-load condition both converters will be activated. The simulation results using LTspice software show that the proposed boost converter has a better efficiency compared to the conventional boost converter with efficiency range of 84.6 % to 95.32 % under various load conditions