PENGARUH PEMBEBANAN TERHADAP EFISIENSI DAN SUSUT UMUR TRANSFORMATOR STEP UP 6kV / 70kV DI PLTU SUMBAWA BARAT UNIT 1 DAN 2 2×7 MW PT.PLN (PERSERO) UPK TAMBORA

This study aims to determine the magnitude of the fluctuating load factor on the efficiency and loss of life of the 6kV/70kV transformer and to determine the optimal load in order to obtain the best efficiency and minimize loss of life. The method used in this study is a quantitative research method. The results showed that the highest efficiency of PLTU Unit 1 was at 93.3% with an output power of 5.8 MW and an input power of 6.21 MW, while the lowest was at 83.9% with an output power of 5.5 MW and a power 6.55 MW input. The highest efficiency of PLTU Unit 2 is at 95.7% with an output power of 5.5 MW and an input power of 5.75 MW, while the lowest is at 61.03% with an output power of 3.3 MW and an input power of 5.41. MW. Meanwhile, the transformer life for Unit 1 PLTU Sumbawa Barat is 0.0469 hours/day with an average load of 5.8 MW, while for Unit 2 it is 0.0311 hours/day with an average load of 5.2 MW. The size of the loss of life of the transformer depends on the given load, the greater the load, the greater the loss of life. In this case, the load for Unit 1 is higher than for Unit 2, so it can be seen that the life loss of the Unit 2 transformer is smaller. While the optimal load on the PLTU is in the position of 80-85% of its capacity. The results of this study are expected to be a material consideration for the Sumbawa power plant to better distribute and optimize the load so that there is no imbalance between the transformer capacity and the power produced and perform routine transformer maintenance to reduce losses that occur.

Low-cost and Efficient Fault Detection and Protection System for Distribution Transformer

Distribution transformers are a vital component of electrical power transmission and distribution system. Frequent Monitoring transformers faults before it occurs can help prevent transformer faults which are expensive to repair and result in a loss of energy and services. The present method of the routine manual check of transformer parameters by the electricity board has proven to be less effective. This research aims to develop a low-cost protection system for the distribution transformer making it safer with improved reliability of service to the users. Therefore, this research work investigated transformer fault types and developed a microcontroller-based system for transformer fault detection and protection system using GSM (the Global System of Mobile Communication) technology for fault reporting. The developed prototype system was tested using voltage, current and temperature, which gave a threshold voltage higher than 220 volts to be overvoltage, a load higher than 200 watts to be overload and temperature greater than 39 degrees Celsius to be over temperature was measured. From the results, there was timely detection of transformer faults of the system, the transformer protection circuits were fully functional, and fault reporting was achieved using the GSM device. Overall, 99% accuracy was achieved. The system can thus be recommended for use by the Electricity Distribution Companies to protect distribution transformers for optimal performance, as the developed system makes the transformers more robust, and intelligent. Hence, a real-time distribution transformer fault monitoring and prevention system is achieved and the cost of transformer maintenance is reduced to an extent.

Power Transformer Fault Severity Estimation Based on Dissolved Gas Analysis and Energy of Fault Formation Technique

Decision making on transformer insulation condition based on the evaluated incipient faults and aging stresses has been the norm for many asset managers. Despite being the extensively applied methodology in power transformer incipient fault detection, solely dissolved gas analysis (DGA) techniques cannot quantify the detected fault severity. Fault severity is the core property in transformer maintenance rankings. This paper presents a fuzzy logic methodology in determining transformer faults and severity through use of energy of fault formation of the evolved gasses during transformer faulting event. Additionally, the energy of fault formation is a temperature-dependent factor for all the associated evolved gases. Instead of using the energy-weighted DGA, the calculated total energy of related incipient fault is used for severity determination. Severity of faults detected by fuzzy logic-based key gas method is evaluated through the use of collected data from several in-service and faulty transformers. DGA results of oil samples drawn from transformers of different specifications and age are used to validate the model. Model results show that correctly detecting fault type and its severity determination based on total energy released during faults can enhance decision-making in prioritizing maintenance of faulty transformers.

Evaluation of Low Cost Piezoelectric Sensors for the Identification of Partial Discharges Evolution

Transformers are essential equipment in electrical energy systems and their failure may lead to the loss of a power supply. Both industry and science have sought to develop sensors and low-cost solutions for the correct diagnosis of their failures. Thus, the use of piezoelectric sensors in the diagnosis of partial discharge in power transformers has been growing significantly, in order to ensure the reduction of maintenance costs, as well as the quality of electric power supply, since this type of failure can lead to a significant cost of repair. In many cases, when partial discharge is detected, there is no immediate need to promote transformer maintenance. In this way, it becomes reasonable to study the evolution of this phenomenon, so that the maintenance of the device can be scheduled and performed correctly. In this regard, this article presents a feasibility study of a low-cost piezoelectric transducer for the identification of the evolution level of partial discharges. For this purpose, in a 30 kVA distribution transformer, three corona partial discharges were produced under three different voltage levels, using a copper electrode. The low cost piezoelectric sensor was coupled to the transformer housing. The acoustic emission signals of the three partial discharge levels were captured and analyzed by the use of acoustic signal metrics, such as energy, peak value, and power spectral density. The experimental results indicated that the low cost sensor is able to identify the evolution of the partial discharge intensity, since the values obtained by the metrics are directly related to the partial discharge levels. Therefore, the results reported in this study indicate that the piezoelectric transducer has a great applicability in diagnosing the partial discharges evolution, and, thus, can assist in the planning of electrical maintenance.