Pengaruh Harmonik Akibat Pengoperasian Motor Induksi Tiga Fasa Pada Sistem Tenaga Satu Fasa

The research conducted focuses on analyzing the harmonic effects resulting from the operation of a three-phase induction motor in a single-phase power system and examining changes in harmonic values due to load variations using two capacitors. This study is a continuation of previous research, which only addressed the influence of a single capacitor on a three-phase induction motor in a single-phase power system, without further exploration of the extent of harmonic impact on the motor. The induction motor operates based on the principle of magnetic induction. This investigation employs a single-phase induction motor with lower power capacity compared to a three-phase induction motor. Three-phase induction motors have a small starting torque, preventing them from starting under full load. The study involves increasing the starting torque of the three-phase induction motor and operating it in a single-phase electrical power system using capacitors to improve power factor during the starting process while analyzing its harmonic effects. The research findings indicate that as the load on the motor increases, both the motor speed and harmonic current values decrease. This is evident when there is no load, and the motor speed is 1475 rpm; adding a load does not exceed this speed. The motor speed decreases as the load increases, while the presence of harmonic current values is due to the linear load, such as incandescent light bulbs. The study is conducted by enhancing the starting torque of the three-phase induction motor, imposing a significant load. The motor demonstrates more optimal and stable performance with the new method compared to the old method. Additionally, the harmonic current values with the new method are lower than those with the old method

Perancangan Antena MIMO 8x8 Frekuensi Kerja 3,5 GHz Untuk Teknologi 5G

The 8×8 MIMO antenna is designed and simulated using CST Studio Suite 2019 software, which generates a visualization using MATLAB software. After optimization, the measurement and simulation of the return loss parameters at a frequency of 3,5 GHz yielded results of -11,85 dB and -31,57 dB respectively. In addition, there are several other frequency ranges with values below -10 dB, such as between 3,047 GHz and 3,243 GHz, 3,438 GHz and 3,925 GHz, and 4,575 GHz and 5,095 GHz. The measured VSWR is 1,668, while the simulation results show a VSWR value of 1,054. In addition, the Mutual Coupling simulation result is -13,16, while the Mutual Coupling measurement is  -28,53, with ECC values of 0,0005 and 0,0002, respectively

Gangguan Saluran Transmisi di Deteksi Menggunakan Metode Gelombang Berjalan dan Transformasi Wavelet Diskrit

Determination of fault location using impedance-based methods and the traveling wave method. Many previous studies used the impedance method but found deficiencies; if the fault impedance is high, it affects the accuracy of determining the fault location. Another method uses the global positioning system (GPS), which is less economical because it requires a lot of expensive devices. This research focuses on the traveling wave method popularized by Bewley, which uses high-frequency electromagnetic impulses derived from transient voltage and current faults inside and outside the line. This method ignores the fault type, line resistance, and fault start angle. In analyzing the time difference between the incident and reflected waves, a discrete wavelet transform analysis is used to help determine the location of the disturbance. The Maninjau hydroelectric power plant and the Pauh Limo substation are modeled using an alternative transient program (ATP) with several components and parameters. Modeling is given for one-phase ground disturbance, two-phase ground disturbance, two-phase, three-phase, and lightning surge. Determination of fault locations using single-ended and double-ended methods with a sampling rate of 1 Mhz by varying the type of wavelet (Daubechies 4, Coiflets 4, Symlets 4) The results obtained in determining the location of disturbances based on the type of wavelet, Daubechies 4, have a small error, so the accuracy is high, and the method double ends for all types of interference to obtain a smaller error rate

Peramalan Beban Listrik Kabupaten Pesisir Selatan Dengan Analisis Regresi

The more electric vehicles emerge, the more electricity demand will increase in each region. This will encourage electricity providers to increase the number or capacity of generators. The construction of a new power plant requires load forecasting to determine how much capacity the plant will build. This study aims to predict the electrical load in Pesisir Selatan, West Sumatra until 2031 using linear regression analysis and time series. Forecasting is done on each sector of PLN customers. Forecasting is done based on the PLN customer sector. The forecasting sectors are the household, business, social and government sectors. The four test criteria were carried out are namely the coefficient of determination test (R2), the F test, the T test and the mean absolute percentage error (MAPE). The forecasting results show that in 2031 the electricity load for the household sector is 120.1 MW, the business sector is 5.7 MW, the social sector is 56.9 MW and the government is 9.5 MW

Reduksi Harmonisa Pada Saluran Distribusi Tenaga Listrik Dengan Filter Daya Aktif

The large use of power converters in distribution lines causes poor power quality such as high produces harmonics in an electric power system that arises due to the operation of non-linear electrical equipment. The presence of harmonics in the power system distribution results in a very large loss in the system. In this paper had been done a simulation of power quality improvement through harmonic reduction using parallel active power filter. Active power filters work with control techniques based on the concept of instantaneous power to determine the amount of compensation currents that must be generated by the power compensator power circuit. The compensating current references generated by the control circuit are used by the hysteresis type controller to provide harmonic compensation arising. From the result of simulation using Simulink MATLAB, the harmonic value (THD) decrease caused by the 3 phase rectifier load on a distribution network which is used as case example. The harmonic value before compensated on the network is 27.85% at each phase, while after computing the harmonic value of the network decreases to 1,43% in R phase, 1,49% in S phase, and 1,34% in T phase. &nbsp

Antena Ultrawideband Multiple Input Multiple Output (MIMO) Dengan Struktur Dekopling Pada Ground

The advancement of technology demands an acceleration in data transmission, where the utilization of UWB MIMO presents a solution to address this issue. However, the implementation of MIMO techniques involving multiple transmitters and receivers leads to an increase in mutual coupling values. This results in a decline in antenna performance. Therefore, a decoupling structure on the ground is employed to minimize mutual coupling values and enhance isolation. The progress of technology calls for expedited data transmission, where the utilization of UWB MIMO presents a solution to address this issue. However, the use of MIMO techniques with numerous transmitters and receivers escalates mutual coupling values. This subsequently leads to a degradation in antenna performance. Hence, a decoupling structure on the ground is employed to minimize mutual coupling values as much as possible and enhance isolation. In this research, a UWB MIMO antenna was designed utilizing a 30 × 40 mm FR-4 Epoxy substrate with a thickness of 0,8 mm and a dielectric constant of 4,4. The antenna was designed using CST Studio 2019 software, followed by fabrication, and subsequently, a comparison was drawn between the simulation and fabrication results.The obtained results have fulfilled the UWB antenna specifications within the frequency range of 3,07 GHz to 11 GHz, with simulated mutual coupling values lower than -15 dB and an envelope correlation coefficient (ECC) value less than 0,01. The resulting radiation pattern is omnidirectional. During the measurements, mutual coupling values of less than -15 dB and good isolation is found within the frequency range of 4,3 GHz to 11 GH

Pemanfaatan Yolo Untuk Deteksi Hama Dan Penyakit Pada Daun Cabai Menggunakan Metode Deep Learning

Chili plants are one of the horticultural crops in Indonesia which have great potential in the Indonesian economy. However, crop failure often occurs. One of the main factors causing this is pest and disease attacks on chili plants. This requires early prevention which can reduce losses. With today's technological developments, prevention can be done easily and economically by using deep learning methods. YOLO is a deep learning algorithm that is commonly used to detect objects in real time. There are 4 classes that will be tested, namely leaves affected by yellow virus disease, leaf spot, thrips pests, and healthy chili leaves. Testing was carried out with a web-based application created with the flask framework. The accuracy results of the YOLO model training process with epoch 150 were 73%. The precision, recall and mAP values ​​obtained were 77.4%, 67.1% and 75.1%. Testing produces accuracy above 74%. The results of this research still produce accuracy that is not high enough, but the application can be used to detect it well and is quite accurate

Alat Pencegah Dini Kecelakaan Pada Kendaraan Bermotor Berbasis Internet of Things (Studi Kasus Jalur Sitinjau Lauik)

The creation of an Internet of Things-based motor vehicle early prevetion tool (Sitinjau Lauik Case Study) has been completed.. The aim of this research is to develop a tool to minimize accidents caused by human physiological factors such as fatigue and drowsiness. This device utilizes the MPU 6050 sensor, pulse heart sensor, buzzer, vibration motor, GPS, Arduino Uno and Wemos D1 Mini. The research method began with the construction of the device and the permance testing of the system. The results indicate that the system of this device can detect drowsiness or fatigue by measuring the heart rate at less than 70 bpm using the pulse heart sensor and detecting head movements using the MPU 6050 sensor, where the X- axis angle is > 29,23 ° < - 30,63 ° and the Y-axis angle is > 29,33° < -20,12°. When drowsiness is detected, the device sends notifications via the Telegram application containing the driver’s condition, heart rate, andlocation through a Google Maps link. Subsequently, when the driver is drowsy, the buzzer sounds to provide a warning and the vibration motor provides vibration to give a sensory wake-up signal to the driver, helping to awaken them from a drowsy state. Overall, the device functions effectively

Karakteristik Medan Listrik-Dekat Petir Positive Cloud to Ground

This study was conducted on 19 electric field data near positive lightning cloud to ground (+CG). The electric field change of +CG lightning consist of preliminary breakdown (PB) and return stroke (RS). The analysis conducted in this research are: PB/RS ratio, PB-RS separation, pre-return stroke duration, pulse train duration, and individual pulse duration. Furthermore, the relationship between +CG lightning and cloud image satellite was observed the average value of PB/RS ratio, PB-RS separation, prereturn stroke duration, pulse train duration and individual pulse duration were 13,89%, 91,53 ms, 102,23 ms, 1,20 ms,150,31 μs, respectively

Prediksi Daya Listrik Pada Pembangkit Listrik Siklus Gabungan Berdasarkan Kondisi Lingkungan Menggunakan Metode Machine Learning

The utilization of machine learning methods in energy simulation enables the optimization of energy use and improves energy efficiency. In this research, the modeling of predicting power output was conducted under full load conditions in a Combined Cycle Power Plant (CCPP) based on the surrounding environmental conditions. Historical data of CCPP operation were used to model and predict power output under various environmental conditions. In this study, four machine learning algorithms, namely Linear Regression (LR), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN), were compared and evaluated for their performance. The evaluation metrics used to measure the model performance were Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-Squared. The research results indicate that the Random Forest (RF) model achieved the best performance compared to other models with MAE of 2.314, RMSE of 3.372, and R-squared of 0.961. Additionally, the RF model also performed the best compared to other models in external testing with new data, where RF obtained values of MAE 2.579, RMSE 3.315, and R-squared 0.957. These results are consistent with the previous testing, indicating that RF has stable and reliable performance in predicting larger and more diverse datasets. This research contributes to understanding the potential application of machine learning in the power generation industry, especially in CCPP