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Integration of Artificial Intelligence for Enhanced Coordination of DOCR Protection in Distributed Generation Systems
Full text linkDistributed generation (DG) is an approach that involves adding decentralized power generation within a distribution network. Distributed generation systems can reduce transmission losses, increase the reliability of energy supply, minimize carbon emissions, and enable the active participation of consumers in energy production. However, with the increase in distributed generation, electric power systems face new challenges in maintaining operational reliability and safety. Disruptions such as short circuits or overcurrent can occur in the system, and appropriate protective responses are required to protect the power grid from more significant damage. The addition of DG also causes the short circuit current to vary and results in system protection coordination having to be redone. Carrying out coordination will take a long time. This research uses modeling and simulation of a distributed generation system with various operating conditions and works adaptively according to changes in the system due to the addition of DG. The results obtained from the simulation are used in neural network training to study the relationship patterns between directional overcurrent relays (DOCR) parameters and system operating conditions. The backpropagation algorithm is used in the Artificial Neural Network (ANN) training process. The training process utilizes the maximum Short Circuit Current (ISC) input obtained through generation, fault location, and fault type. Time Dial Setting (TDS) and Ipickup values are used as ANN training targets. After testing, the results obtained are in accordance with the target data. The efficacy of this method is further demonstrated through ETAP simulations, which confirm that ANN is a suitable approach for modeling adaptive and optimal relay coordination systems
Forklift Design Integrated Speed Limiter and Position Tracking Through IoT-Based Website
Full text linkForklifts, as lifting and transportation equipment, play a crucial role in logistics. However, forklift operators often chase targets, pushing the forklift to perform at higher speeds. Operating a forklift at high speeds not only poses potential dangers to the working conditions but can also lead to a decrease in forklift performance. Operators do not ensure the forklift is running according to procedures due to a lack of supervision. In response to this issue, the author proposes an innovation in the form of a monitoring device capable of recording speed violations committed by operators. With the planned device, it is expected that forklift operators will exercise more caution and take greater responsibility when operating the forklift. The objective of this research is to reduce the likelihood of accidents and forklift damage due to improper use. The study produces a forklift design equipped with supporting components for the implementation of the device and a website as a monitoring platform for forklift operators and workers, providing real-time access to collected data. This system enhances operational safety in operating forklifts. The research significantly contributes to the development of safer and smarter forklift technology, aligning with strict demands for safety standards and risk management in industrial environments
Performance Analysis of Permanent Magnet BLDC Motor for Reducing Cogging Torque Using Taguchi Method
Full text linkAn electric motor is an electromagnetic machine commonly utilized across various industries and automotive products. One prevalent type of electric motor employed in electric vehicles is the Permanent Magnet Brushless DC Motor (PM-BLDC), a brushless motor employing permanent magnets. However, despite its efficiency, permanent magnet motors often experience vibrations that can disrupt their performance. This research aims to optimize the existing BLDC motor design, with a specific focus on reducing the existing cogging torque. Initially, the existing design exhibited a cogging torque level of 0.21482 Nm. The optimization process involved modifications to several key design parameters, such as air gap, magnet thickness, magnet type, and slot opening width. In previous research, only comparisons were made between stator slot designs, which proved to be less effective as significant differences were not evident in the results of the comparative analysis of BLDC motor designs. So, in this research, the Taguchi method was utilized for the optimization process due to several advantages it offers. Through an analysis of means and variance, the optimization process successfully achieved a significant reduction in cogging torque by 0.099744 and an increase in efficiency by 0.6%. The results of the optimized permanent magnet BLDC design indicated a cogging torque value of 0.115072 Nm and an efficiency of 86.64% at an operational motor speed of 1500 rpm. This research provides a substantial contribution to the development of more efficient electric motors suitable for various applications
Development of Salted Egg Maker by Using PLC Based on Osmotic Pressure Method
Full text linkSalted egg is one of the egg types that has a lot of devotees because it tastes a little salty and savory. Salted eggs are usually homemade in various regions. The easy process of making them has attracted many people to do so. This study developed a PLC-based on automatic system for a salted egg maker using the osmotic pressure method to accelerate the opening of the semi-permeable membrane on duck eggshells so that the salting mixture seeps into the eggs more quickly. It was carried out in an osmotic pool containing water and acetic acid at a concentration of 5%. The data collection process in designing the salted egg maker consisted of evaluating the performance of photoelectric sensors, proximity sensors, temperature controller, thermostat set point, baking time, and salted egg durability test. The results of the tests indicated that the time needed to make salted eggs from raw eggs to cooked eggs only took 36 minutes using the machine designed. Additionally, the presented salted egg maker reveals the short making time, and long salted egg durability. altogether revealing full potential to be easily used for practical applications
Optimal Propagation Model for DVB-T2 System in Urban Area
Full text linkThe large-scale implementation of analog switch-off for television broadcasting in Indonesia has led to blank spots in several regions. To address this issue, an optimal propagation model is needed. Proper selection and analysis of the channel model can enhance transmitter coverage, increase coverage percentage, improve energy efficiency, and boost field strength due to optimal transmit power. Previous studies have explored various DVB-T2 propagation models, notably the ITU-R P.1812-4 and Longley-Rice models, which are sophisticated and consider various environmental parameters, making them suitable for diverse broadcasting conditions. This research introduces a novel approach by specifically focusing on the urban context of Semarang City, Indonesia, to reduce blank spots by applying the ITU-R P.1812-4 and Longley-Rice propagation models. This study uniquely compares the two models to determine the most effective one for this urban area. Results indicate that the ITU-R P.1812-4 model provides a higher field strength value than the Longley-Rice model, with average field strengths of 108.3425 dBμV/m and 108.2325 dBμV/m, respectively. The difference in average field strength of 0.11 dBμV/m, despite having the same free space loss value of 100.9025 dB, indicates that one model has a slightly stronger signal. This stronger signal can improve coverage by reaching further distances and penetrating obstacles better. Additionally, a stronger signal means less power is needed to maintain the same coverage area, thus improving energy efficiency. This research not only offers empirical data specific to Semarang City but also provides insights that can guide future digital broadcasting optimizations in similar urban environments
Design of Electric Motorcycle Variable with Battery Management System
Full text linkThis study focuses on conceptualization and development of a battery management system (BMS) with two main functions, battery monitoring and management, in the context of brushless direct current motors (BLDCs). The main challenge in variable estimation is to protect the battery from potential risks during the charge and discharge cycle. The new proposed resolution combines a comprehensive BMS with monitoring capabilities for charge (SoC), health (SoH), voltage, current and battery temperature. In addition, a protective mechanism is incorporated to prevent variables from overshooting safety parameters. This research uses two different methodologies for estimating SOC, coulomb counting and open circuit voltage. In experimental tests, resistance potentiometers of 1,650, 3,300 and 0 were used, with SoC estimates of 37%, 19% and 65%, while coulomb counting method has a marginal error of 1.13%. On the contrary, the open-circuit voltage method generated a SoC estimate of 0% for all potentiometer resistance, with an error rate of 0.64 %. As a result, the open circuit voltage method is chosen because of its superior accuracy compared to the coulomb counting method. The state assessment of the battery showed a value of 100% after seven cycles. In addition, a protective system has been implemented to ensure that battery variables remain within the safe thresholds throughout the charge and discharge process. Consequently, the implementation of this BMS is expected to significantly improve overall performance and extend battery life
PID Controller with an Override Mode for a Wall-Following Robot with a Rotating Sensor Compartment
Full text linkThis paper presents the design of a wall-following robot (WFR) with a rotating sensor compartment to reduce the number of distance sensors used. Two infrared (IR) sensors were fitted in the compartment that rotates back and forth at 45°, producing four measurement values at each rotation cycle. The WFR was regulated using a novel control scheme of PID controller with an override mode. A discrete PID controller in position form was used to run the WFR to follow straight wall segments or walls turning left, while an override mode governed the WFR to follow walls turning right. The sampling time was set to 300 ms. The parameters of the PID controller were tuned using a trial-and-error method. The Mean Absolute Errors (MAE) was selected as the cost function. The WFR conducted twelve trial runs along a trial track with a length of 200 cm, consisting of one right turn and one left turn. The parameters that yielded the lowest MAE of 0.90 cm were used for further tests. Subsequently, a closed track for testing was constructed with a length of 845 cm, consisting of 7 right turns and 2 left turns. The WFR completed five test runs successfully, each elapsing the test track twice. The lowest MAE during the tests was 1.06 cm. The favorable performance of the proposed WFR strengthens future development efforts to equip the robot with more hardware to fulfill specific tasks and to put the completion time into optimization consideration
Multi-oscillations Detection for Process Variables Based on K-Nearest Neighbor
Full text linkIn the process industry, a control system is important to ensure the process runs smoothly and keeps the product under predetermined specifications. Oscillations in process variables can affect the decreasing profitability of the plant. It is important to detect the oscillation before it becomes a problem for profitability. Various methods have been developed; however, the methods still need to improve when implemented online for multi-oscillation. Therefore, this research uses a machine learning-based method with the K-Nearest Neighbour (KNN) algorithm to detect multi-oscillation in the control loop, and the detection methods are made to carry out online detection from real plants. The developed method simulated the Tennessee Eastman Process (TEP), and it used Python programming to create a KNN model and extract time series data into the frequency domain. The Message Queuing Telemetry Transport (MQTT) communication protocol has been used to implement as an online system. The result of the implementation showed that two KNN models were made with different window size variations to get the best performance model. The best model for multi-oscillation detection was obtained with an F1 score of 76% for detection
Design of Smart Home Security System With Face Recognition And Voice Command Based On Internet of Things
Full text linkAll individuals really need technology to accelerate development or enhance the development of both individuals and groups. A smart door lock is a feature embedded in a smart home to make everyday life easier. Given the importance of security for valuables stored in the house and the fact that security is required in accessing the house, the research was conducted with the goal of helping meet the needs of an easy-to-implement home security system. By utilizing the Raspberry Pi minicomputer as a processor, the webcam as a face detector, and Voice Command for detecting voice codes, which will then be processed by the Raspberry Pi using OpenCV to determine whether a human face is there or not, calculating the distance between facial features such as eyes, nose, and mouth as well as the code, the given vote is either true or false. After the face is recognized and the sound code is correct, the Raspberry Pi will issue an order to the servo to open the solenoid so that the home door can be accessed by the home owner, and there will be a message sent via telegram if someone tries to access this system. Based on the system tests that have been carried out, it turns out that the facial recognition system has an accuracy of 75%, a positive error of 25%, and a negative error of 0%, so it can be concluded that this system is safe enough to be applied in a home door security system
Design and Implementation of 12-Bit Arithmetic Logic Unit with 8 Operation Codes to Field Programmable Gate Array
Full text linkDigital system has been a part of human life since the invention of the computer with a microprocessor as the central brain. At the heart of a processor is an Arithmetic Logic Unit (ALU) that handles arithmetic and logic operations. The need for high-speed computation to handle complex computations demands microprocessors with higher performance. The existing 4-opcode 8-bit ALU cannot handle multiplication operations, so a solution is needed. In this research, while raising the appeal of beginners, a 12-bit ALU with eight operation codes (opcode) was designed and implemented in Xilinx’s Field Programmable Gate Array using a schematic diagram approach through logic gates. The designed and implemented ALU provides addition, subtraction, multiplication, square, AND, OR, NAND, and XOR operations. The multiplication operation was tested by performing the computation to provided datasets to obtain the distance travelled by ten military aircraft based on their maximum speed and air travel duration to ensure its performance. The computation performance comparison with an 8-bit ALU with four opcodes was also done. The computation was done for air travel between 10 to 60 minutes with a 10-minute difference. It was found that the 12-bit ALU with eight opcodes outperformed its contender with computation differences between 130.815 ns and 1,468.214 ns. This high performance is supported by the multiply operation that does repeated addition at one time. Based on this finding, the 8-opcode 12-bit ALU is more efficient in the context of computation time, with consistent accuracy. Moreover, the computation time required to calculate military aircraft data with different maximum speeds and air travel duration is only 119.501 ns