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Design and Manufacture of Wireless Monitoring system of Photovoltaic Generation Employing Raspberry PI 3
Full text linkThis paper recounts design and development the realtime and wireless monitoring systems to observed the characteristics and performanced of the solar photovoltaic (pv) energy generation. The monitoring systems designed used the Raspberry Pi 3 as the data processing center, the voltage divider as the voltage sensor, ACS712 as the current sensor, DHT as the temperature sensor, and BH1750 as the solar irradiation sensor. The measurements of the pv generation characteristics are carried out all the time in real time. The monitoring systems developed has calibrated with standard measuring instruments. The measurement data has processed, sent and stored in the database via the internet. The MySQL database with single user interface using the Web-based programming language has employed. This research has proven that the system designed to functioning properly and correctly to achieve the objectived. The novelty of these project are the pv wireless monitoring systems techniques with the simple device resources, capable of showing maximum performanced
Electrical Conductivity of Conducting Polymer Composites based on Conducting Polymer/Natural Cellulose
Full text linkMerging each of the best properties of components into a composite design or hybrid architecture opens up opportunities to develop electroconductive materials as conducting polymer composite. This work deals with studying the electrical conductivity of conducting polymer composites made of cellulose extracted from two biomass: empty fruit bunch from oil palm and peat soil. Two kinds of conducting polymers have been used to fabricate the composites, i.e. polyaniline and polypyrrole, which are polymerized from their monomers, aniline and pyrrole. The novelty of this research is the using of biomass as the source of cellulose to produced conducting polymer composites by adding conducting polymer as filler into polymer matrix. We report experimental studies about the influence of monomer addition on the electrical conductivity of composites produced. The conductivity of the material was measured by using the Electrochemical Impedance System method. The experiments were carried out as a four-set experiment, using two different cellulose sources, EFB and peat soil, combined with aniline and pyrrole. The mass ratio variations of the monomer: cellulose are 1, 2, 3, and 4. The conductivities of the composites increased when more aniline or pyrrole was blended with the extracted cellulose from each source, either EFB or peat soil. The conductivity of composite PANI/EFB, which is 3.5 ´10-3 - 1.1´10-2 S/cm, is in the semiconductor range that makes the composites useful for many applications
Reliability Analysis and Maintainability for the Design of Grid and Hybrid Solar Power Plant Systems in Wonogiri Regency
Full text linkIndonesia has the potential for large solar power plants. It has relatively constant solar radiation because it is close to the equator. Besides, solar energy includes renewable energy that is more environmentally friendly and easier to apply in office areas, especially Wonogiri. However, it turns out that the solar power plant projects that have been built are not yet fully functional, and some have even failed. A lack of responsibility and maintenance causes this carried out after the project is complete. For this reason, it is necessary to estimate the reliability of these components and determine the maintenance schedule before the project is carried out. So that later they have a picture and be better prepared when this project is already underway. The fault tree method's failure factors are expected to create a picture to maintain reliability and determine the prioritized components for maintainability. For the results obtained to be more appropriate, apart from seeing the quantitative analysis output, the fault tree also needs to be adjusted to the component manual or datasheet to determine the replacement of spare parts and their maintenance. So that the resulting schedule for maintenance and replacement of spare parts. Thus, the solar power plant project that has been built will be more reliable and can be appropriately utilized
Humanoid Robot Application as COVID-19 Symptoms Checker Using Computer Vision and Multiple Sensors
Full text linkNovel Corona Virus (nCoV) infects human’s respiratory system. It spreads easily when an infected person makes a close contact with other people. To prevent its massive spread, it is necessary to ensure anyone coming to a certain place is not being infected. The symptoms include high body temperature (≥37.5°C) and low oxygen saturation level (≤95%). This day, most places only check the human body temperature. Thus, the authors are interested to make an attempt to design a system that is able to measure both human body temperature and oxygen saturation level. This work also applies the 7-DoF Upper-Body of Humanoid Robot to prevent virus spread from and to the employee. The system will detect the coming of visitors by using face detection. It requires 7.24 seconds to detect the visitor without a mask, and 1.26 second when the visitor wears a mask. The body temperature measurement was done using GY-906 temperature sensor with an error of 0.51%. For the oxygen saturation level measurement, MAX30100 pulse oximeter module was applied and showed an error of 0.78%. In addition, the upper-body of humanoid robot will perform some gestures to instruct the visitors in every process of the system. The implemented 7-DoF upper-body of humanoid robot has 93.33% gesture comprehension rate. In conclusion, the overall system has been tested and showed success rate up to 75%
Reliability Evaluation of Kumpai Feeder Distribution System at PT. PLN (Persero) ULP Siantan
Full text linkThe research on reliability index of a feeder aims to evaluate the reliability level of a feeder using the Reliability Index Assessment (RIA) method. This method evaluates the reliability of a 20 kV distribution network by calculating the reliability indexes of each load point. The evaluation results show the reliability index value per section of the Kumpai Feeder at PT. PLN (Persero) ULP Siantan within one year. The SAIFI values are 0.0092; 0.0012; 12,477; 0.0596; 0.0204; 0.0470; 0.0155; 0.0728, the SAIDI values are 0.0277; 0.0042; 37,746; 0.1862; 0.0741; 0.1524; 0.0493; 0.2209, the CAIDI values are 3.0108; 3.5; 3,025; 3.1241; 3.6323; 3.2425; 3.1806; 3.0343, the MAIFI values are 0; 5,480; 0.2145; 0.0020; 0.0038; 0.0042; 0.0006; 0.0014. The calculation results show that the 20 kV distribution system at PT. PLN (Persero) ULP Siantan at the Kumpai Feeder can be categorized as unreliable. Because the SAIFI value of this feeder exceeds the standard set by PT. PLN (Persero) which are 12.477 times/customer/year and 3.2 times/customer/year, respectively. The factors affecting the reliability index of the Kumpai feeder are the number and duration of blackouts, the number of customers, and the length of the distribution system channel
Performance Analysis of VRLA Battery for DC Load at Telecommunication Base Station
Full text linkThe high level of power outage in Sukabumi-Cianjur area has influenced the operations of telecommunication industry in the vicinity. This has shortened the battery life at the Base Station (BTS). This study aims to analyze the performance of a (new) VRLA battery against a DC load (BTS) to support the continuity of BTS operation in case of a power outage. The research method used is a (new) battery charge-discharge procedure. Parameters are analyzed by determining the on-site battery discharge duration, the pressure at the battery terminals between cells during backup, and the capacity of the rectifier module to support fast charging. To support fast charging, the rectifier with the formula N+1 and C-rate is 10% and C15 is 15% of the battery capacity. The internal impedance value is 3.4 mΩ and the battery terminal pressure (torque) is 9-11 N/m. The battery performance analysis of the four BTS shows that two of them managed to do a backup, while the other two did not provide good performance
Performance and Analysis of Indirect Torque Control-Based Three-Phase Induction Motor
Full text linkInduction motors are widely used in industrial processes, vehicles and automation. Three-phase induction motors can be used for traction systems on electric locomotives. In this case, the speed control system is an important thing that must be applied to the propulsion system. This study aimed to test the indirect torque control for a Three-phase induction motor. A proportional integral (PI) controller was applied for speed controller. The indirect torque control system was modeled and simulated using PSIM software. According to the result, the control method showed a good performance. The speed could be maintained even the speed reference was changing or a load was applied. The steady state error of the speed response was just 0.1% with rise time around 0.06 s. The stator current went up to 39.5 A in starting condition. The stator current reached 12 A rms when the load of 10 Nm was applied. Then, the current rose to 15.7 A rms when the load was increased to 40 Nm and the current came down to 12.8 A rms when the load was decreased to 20 Nm
Comparison and Analysis of Neural Solver Methods for Differential Equations in Physical Systems
Full text linkDifferential equations are ubiquitous in many fields of study, yet not all equations, whether ordinary or partial, can be solved analytically. Traditional numerical methods such as time-stepping schemes have been devised to approximate these solutions. With the advent of modern deep learning, neural networks have become a viable alternative to traditional numerical methods. By reformulating the problem as an optimisation task, neural networks can be trained in a semi-supervised learning fashion to approximate nonlinear solutions. In this paper, neural solvers are implemented in TensorFlow for a variety of differential equations, namely: linear and nonlinear ordinary differential equations of the first and second order; Poisson’s equation, the heat equation, and the inviscid Burgers’ equation. Different methods, such as the naive and ansatz formulations, are contrasted, and their overall performance is analysed. Experimental data is also used to validate the neural solutions on test cases, specifically: the spring-mass system and Gauss’s law for electric fields. The errors of the neural solvers against exact solutions are investigated and found to surpass traditional schemes in certain cases. Although neural solvers will not replace the computational speed offered by traditional schemes in the near future, they remain a feasible, easy-to-implement substitute when all else fails
Design of a Fuel Sensor Noise Reduction System Using Kalman Filter
Full text linkIn the field of transportation, telematics is used to obtain vehicle information using Global Positioning System (GPS) technology which is integrated with sensors so that vehicle information can be monitored. One of them is fuel monitoring. The fuel sensor has good accuracy in stationary conditions, but the tability of the data is disturbed when the vehicle is running on an uneven road and causes the tank to shake. This study discusses a fuel sensor noise reduction system using a Kalman filter to overcome the problem of data instability due to shocks. This research aims to reduce noise so that the filter results are closer to the actual result. Filtering is done by changing the process error covariance (Q) and measurement error (R) in the Kalman filter. The fuel sensor noise is simulated using a simulator tank driven by an actuator that can tilt towards the x-axis and the y-axis to resemble the behavior of a vehicle. The fuel level data from the sensor readings are sent by GPS via the cellular network to a server which is then filtered using a web application. From the test results obtained the best filter with (Q) equals 0.1^3 and (R) equals 0.1^3. The average error of the best filter results is 4.73% where this value is 1.92% smaller than the average error of sensor data before filtering, which is 6.65%. Therefore, this proves that the system can reduce noise that occurs in the fuel sensor with the Kalman filter
Front Matter
No full textPRAKATA :ELKHA merupakan jurnal ilmiah yang diterbitkan berkala dua kali per tahun oleh Jurusan Teknik Elektro Fakultas Teknik Universitas Tanjungpura. Makalah yang dapat dimuat dalam jurnal ini meliputi bidang keilmuan Teknik Kendali, Elektronika, Sistem Tenaga, Telekomunikasi, Informatika, Sistem Distribusi dan Teknik Industri. Makalah dapat berupa ringkasan laporan hasil penelitian atau kajian pustaka ilmiah. Makalah yang akan dimuat hendaknya memenuhi format yang telah ditentukan, contoh terlampir pada halaman terakhir jurnal ini atau dapat menanyakan ke alamat sekretariat jurnal ELKHA. Bahasa yang digunakan pada jurnal ini adalah bahasa Indonesia atau bahasa Inggris. Tanpa mengurangi bobot ilmiah, jurnal ini menerima sumbangan tulisan yang belum pernah diterbitkan dalam media cetak lain dan menerima pemasangan iklan