I Made Yulistya Negara

Optimal placement and sizing of Distributed Generation using Quantum Genetic Algorithm for reducing losses and improving voltage profile

In this paper Quantum Genetic Algorithm (QGA) is combined with The Newton Raphson power flow (NR power flow) to optimize the placement and sizing of Distributed Generations (DGs) in electrical power systems. QGA is used to find the optimal placement and generate real power of DG in accordance with mathematical calculations and NR Power Flow is used to calculate the loss on the network and determine the voltage at bus. The goal is to minimize the losses, while at the same time still maintain the acceptable voltage profiles. DGs may be placed at any load bus. Which load buses to have the DGs and of what size they are respectively are determined using this proposed method. Observations are based on standard IEEE 14 buses input and results are compared to the results of network without DG and network with DG by other methods.

Analisis Karakteristik Arus dan Tegangan pada Inisiasi Feroresonansi Transformator Tegangan Rendah

Ferroresonance is an interaction phenomenon between non-linear inductance and capacitance that initiates abnormal waveform of current and voltage. This phenomenon is very sensitive to system parameter and initial condition. In this paper, ferroresonance initiation involved a basic circuit of series ferroresonance with variation of source voltage magnitude on a single phase low voltage transformer. The scheme of experiment was based on the case of transformer energizing. The trends of current and voltage waveform on the primary windings were investigated and transformed by using Fast Fourier Transform (FFT). The harmonics spectrum was then employed to identify the feroresonance mode and calculate the Total Harmonics Distortion (THD) of current and voltage. The experimental results showed that the higher source voltage magnitude caused the ferroresonance responses to be seen more clearly. It was indicated by the more distorted waveform, the higher odd harmonics frequency amplitude especially for 150 Hz, and the greater THD. Based on the harmonics spectrum and wave period, the ferroresonance responses were identified as fundamental mode. The effects of initial conditions, such as residual flux of transformer and capacitor charge, were also seen on the distorted wave peak during transient condition. In addition, the difference of waveform between normal and ferroresonance condition could be more easily observed on the voltage than the current. The waveforms of current and voltage during experiment had been verified by using simulation.

Estimation of residual flux in single phase transformer using dynamic modeling of two winding single phase transformer

This study deals with estimation of residual flux in 1 kVA 1-phase transformer. Transformers used in the study have two type core cutting topology. The transformers were modeled with MATLAB software and then simulated to obtained inrush current. Experiments were also done in order to obtain its inrush current with different demagnetization time. The result showed a difference between simulated inrush current result and experimental result, which influenced by the existing residual flux and not yet disappeared during demagnetization process on the core of the single-phase transformer. The result shows that different core cutting topology affects the residual flux as well as the time of demagnetization.

Core-cutting topology effects of single phase 1-KVA transformer on inrush current

This paper deals with core-cutting method effects of single phase 1-KVA transformer on its inrush current. Different core-cutting topologies of transformer which is EI and EE were studied. Finite-element method and equivalent circuit based simulation were done to understand its effect on inrush current of transformer. Equivalent circuit is used to obtain the peak value of inrush current. Meanwhile finite-element method simulation is used to understand the distribution of flux density and magnetic field intensity. The results show that inrush current value influenced by core losses. Moreover, it is shown that EI cutting topology gives lower peak value of inrush current.

Analysis of low voltage arcing characteristic on direct short circuit through arcing thermal synchronization sensing and short circuit current

Short circuit fault cause arcing fault initiate fire accident. Fire case caused by short circuit fault in low voltage installation is occured every year. Several cases in fire accident at low voltage installation caused by short circuit fault. In this case, protection equipment failed to detect and secure the installation. This experiment investigate short circuit case at low voltage filament conductor cable 1.5 mm2. Short circuit cases variated by filament or strand that experienced contact. When short circuit occurred, arcing is recorded by thermal camera. Moreover, current and voltage arcing will be synchronized with thermal arcing image. The synchronization result is analyzed to obtain the caharacteristics of arcing that consist of value of maximum temperature arcing, sectional area arcing data, and duration of arcing. These characteristics are very useful to design arcing fault detector. The result shows that the arcing temperature, area, and duration respectively are up to 100 °C, 1300 mm2, 10 seconds.

Analysis of contaminant effect on ceramic & polymer insulator surface under artificial environmental condition

Performance of an insulating dielectric may decrease due to aging. The main cause of aging on insulator is contaminant arising on the insulator surface. In this study, effects of contaminants on the coating large leakage current on the surface of the polymer insulator are investigated. To analyze the effects, accelerated age testing module as a form of pre-conditions on polymer insulator aging is designed. Furthermore, dielectric strength testing is performed to determine the effect of contaminants on pre-breakdown voltage. The results of this study showed that the thickness level of contaminants on the surface of the layer affects insulator leakage current and pre-breakdown voltage.

Analysis of acceleration in aging insulation due to the effect of humidity and contaminant in induction motor loaded

In this study, the experimental of accelerated aging in induction motor insulation is done in a loaded state with high humidity influence and under effects of contaminant. The method used to evaluate the condition of the motor is polarization index (PI), oscillatory response test (surge test) and LCR measurement. PI is used to determine the value of polarization index and custody coil insulation via measured four direct current during the test. Oscillatory response test used to determine differences in the quality of the coil insulation based on the response to the wave oscillation with error area ratio (EAR) method. While the LCR measurement is used to detect the value of inductance, capacitance and resistance arising from the influence of humidity and contaminant in the stators coil. Furthermore, the output PI variable and oscillation response test and LCR measurement compared to getting the tendency chart damage. Based on test results, EAR method is faster to detect decrease coil insulation in the second test by 30.5 %. Meanwhile, the new PI value was changes in its value in the fourth test. While the LCR value is not significant.

Analysis of physical and electrical characteristics of transformer oil insulation during accelerated thermal aging experiment and its lifetime estimation using arrhenius law and breakdown voltage test

In this paper, the physical and electrical characteristics of accelerated thermal aged transformer oil insulation were investigated. The accelerated thermal aging of commercial transformer oil was conducted by increasing its temperature with different time. They were 100°C for 168 hours, 115°C for 96 hours, and 125°C for 48 hours. The lifetime of the tested oil was then estimated based on Arrhenius law and breakdown voltage test. The result showed that the physical characteristic of the tested oil during accelerated thermal aging could be analyzed based on its color changes, in which the higher level of thermal aging resulted in darker oils color. The electrical characteristic was associated with significant decreasing of breakdown voltage. The lifetime estimation based on Arrhenius law for the tested oil with 100°C, 115°C, and 125°C were about 25663 hours, 4300 hours, and 1408 hours, respectively. The lifetime estimation based on breakdown voltage test for the tested oil with 100°C, 115°C, and 125°C were about 20064 hours, 1526 hours, and 1106 hours, respectively.

Comparative analysis of electric field distribution on glass and ceramic insulator using finite element method

This study investigates electric field distribution on different materials used as pin isolator. Those materials are ceramics and glass. Insulators will be 3 dimensionally modeled and e-field distribution will be analysed by using FEM (Finite Element Method). Insulators are conditioned into 3 types, which are normal condition, contaminant condition, and cracking condition. Contaminant used in this study is water which is varied by its contact angle. Meanwhile, cracking condition means some crack occurs on surface insulator. Both conditions are performed on the first fin of the insulator. The analyzis is done by comparing the electric field distribution in both glass and ceramic insulator on those 3 conditions. The results show that ceramic insulator has slightly higher electric field distribution. Moreover, contaminant and cracking affect electric field distribution.

Vibration analysis for the classification of damage motor PT Petrokimia Gresik using fast fourier transform and neural network

The electric motor is an important equipment to use in the industrialized world. Because its function is very crucial, so the damage of this electric motor will directly affect the production performance. In this research, the vibration data of electric motor at PT. Petrokimia Gresik has been classified based on physical damage which is using both of Fast Fourier Transform (FFT) and neural network methods. There are 5 types of conditions to classify the damage of electric motors using a neural network, namely normal condition, unbalance, miss-alignment, looseness, and antifriction. From the results obtained, the differences amplitude values from each condition. This level of accuracy of neural network method for detecting the damage motors in this study is 100% accurate.