Linear Trend Application on the Estimated Age of Distribution Transformer Based on the Load Growth and Environmental Temperature

This research aimed to find the age loss of distribution transformer based on the load growth and ambient temperature to predict the remaining age of the transformer. This research used the remaining estimation age calculation based on load growth that was predicted using the linear trend analysis. The distribution transformer in this research was the BO043 200 kVA, installed in 2012, and was operated in Bolo Feeder, Woha District, Bima Regency. The results showed that the BO043 transformer was operating at the average ambient temperature of 28℃ with the optimum loading threshold of 92.77% from its power rating. The transformer would experience age reduction if the load given were above that value. The calculation results showed that the BO043 transformer had the estimated remaining age of 4 years from the standard 23 years with the 2019 load prediction of 83.39% and up to 115.94% load prediction in 2022.

Study of Technical and Non-technical Factors in Energy Consumption on 20 kV Distribution Networks

This research aimed to find the technical and non-technical losses that occurred on the 20 kV Tawangrejo Feeder network by calculating the electricity losses after measurement and the calculated losses, made an application to calculate the losses, and determined the improvement alternative from the suitable electricity losses. Based on the data analysis, the conclusions were: Tawangrejo Feeder used mesh configuration with a three-phase four-wire construction model. The values of power and energy losses in total, technical, and non-technical were fluctuating, depended on the current value that was sent from the primary substation to the load. This power loss calculation application had a high accuracy because the error occurred at a maximum of 0.0021%. The most effective power loss improvement was replacing the conductor duct that reduces 56% of power and energy losses.

Home Energy Security Prototype using Microcontroller Based on Fingerprint Sensor

The globalization era brings rapid development in technology.The human need for speed and easiness pushed them toinnovate, such as in the security field. Initially, the securitysystem was conducted manually and impractical compared tonowadays system. A security technology that is developed wasbiometric application, particularly fingerprint. Fingerprintbasedsecurity became a reliable enough system because of itsaccuracy level, safe, secure, and comfortable to be used ashousing security system identification. This research aimed todevelop a security system based on fingerprint biometric takenfrom previous researches by optimizing and upgrading theprevious weaknesses. This security system could be a solutionto a robbery that used Arduino UNO Atmega328P CH340 R3Board Micro USB port. The inputs were fingerprint sensor, 4x5keypad, and magnetic sensor, whereas the outputs were 12 Vsolenoid, 16x2 LCD, GSM SIM800L module, LED, andbuzzer. The advantage of this security system was its ability togive a danger sign in the form of noise when the systemdetected the wrong fingerprint or when it detects a forcedopening. The system would call the homeowner then. Otherthan that, this system notified the homeowner of all of theactivities through SMS so that it can be used as a long-distanceobservation. This system was completed with a push button toopen the door from the inside. The maximum fingerprints thatcould be stored were four users and one admin. The admin’sjob was to add/delete fingerprints, replace the home owner’sphone number, and change the system’s PIN. The resultsshowed that the fingerprint sensor read the prints in a relativelyfast time of 1.136 seconds. The average duration that wasneeded to send an SMS was 69 seconds while through call was3.2 seconds.

Evaluation of Power Distribution based on Power Losses on Transmission Interconnection

This paper discusses the analysis of continuity of power delivery and network losses in the scenario of adding 150 kV to the Malang Raya transmission network. The discussion in this paper is based on the increasing load growth conditions in Malang Raya and the condition of the Malang 150 kV main system which is centralized in the Kebonagung Substation so that a scenario of adding 150 kV transmission network interconnection is needed to increase the capacity, reliability, and improvement of the Malang Raya system. Based on the simulation results before the scenario of adding 150 kV transmission network losses in the poor 150 kV main system by 0.02 MW, whereas after the scenario of adding 150 kV transmission network the overall losses in the 150 kV main unfortunate main system were 0.009 MW.

Implementation of Artificial Neural Network Method for Estimating Connected Power and Electric Energy Consumption

Abstract—Electricity is vital for modern society’s welfare. Daily electricity usage depended on the customers’ type. Hence, there was a difference between the connected power with consumption. Therefore, there needed an estimation method for long-term connected power and energy consumption to improve the safety of energy management and operation plan for the generator. This research used the Artificial Neural Network method with a backpropagation algorithm model to estimate the connected power and electricity consumption. This method has the advantage of following past patterns after the training process. This research used data such as total population, Gross Regional Domestic Product, total customers, produced energy, remaining energy, distribution loss, total transformer, peak load, and load factor as the independent data. The energy consumption and connected power served as the dependent data. The data was taken from Srengat Network Service Unit, East Java, for ten years, which started in 2008. This research used literature study, information and data collection, information and data process, data estimation and analysis, and conclusion as the procedures. Based on the results, the best network structure was 9-9-2 with the 10-6 goal, 0.9 momentum value, and 0.15 learning rate to produce the smallest Mean Squared Error of 0.00442 in 2015, Mean Absolute Percentage Error of 7.88% for the connected power, and 11.27% on electricity consumption target.

Monitoring and Controlling The Hybrid System Using The Internet Of Things For Energy Transaction

The electrical energy is an energy that is needed by the people. Theelectrical energy, to date, came from several power plants, such aselectric steam power plants and diesel power plants. The communitymust pay the service provider, such as the State ElectricityCompany (PLN) with a rising cost, to obtain electrical energy.However, there were other alternative energies, for example, solarpower plants and windmill power plants. The hybrid system is acombination of two or more different energy sources to meet thedemand. The hybrid system was also expected to solve the problemthat might arise in utilizing other energies, the site condition, andthe unpredicted situation on the power plant. The solution to theseproblems was a hybrid using a monitoring device with ACS 712sensor current parameter, ZMPT101B voltage sensor, LDR solarsensor, hybrid electrical energy power, controller for four electricalsource inputs and three electrical sources for the output load. Thedevice used Arduino Mega 2560 for data processing, ESP 8266 asthe module to connect the device to the internet network and relayas the control actuator. Monitoring and controlling the device usedthe internet network and the implementation of the Internet ofThings (IoT) on the hybrid system plants (PLN, generator, solarpower plant, windmill power plant) that was integrated into thewebsite. The overall test resulted in the comparison average errorvalue between the device and the measuring instrument of thecurrent, voltage, and power. The test also resulted in the averageerror value of the response time for the four input contacts and threeoutput contacts. The average error value of the current was 2.13%,the average error value of the voltage was 0.7%, and the averageerror value from the power parameter was 0%. Meanwhile, theaverage error value of response time was 0.23 seconds. Based onthe above results, it can be concluded that the monitoring andcontrolling system from the website with the implementation of theIoT in the hybrid power system was worked following the design.

Performance Comparative Analysis of Monocrystalline and Polycrystalline Single Diode Solar Panel Models using the Five Parameters Method

The use of renewable energy as a source of electrical energyincreases every year. Unfortunately, Indonesia does not have manypower plants that utilize renewable energy sources. The mostpotential renewable energy in Indonesia is the sunlight with the helpof solar panels that converts solar energy into electrical energy.However, the environment could affect the solar panel module andin turn, affect the performance of solar panels or the generatedelectric energy. This research calculated the performance of solarpanels with a single-diode model using the Five Parameters methodthat required solar panel module specification data, the totalradiation absorbed by the solar panel module, and the temperatureof the environment. The Five Parameters method is a methodmodeled after solar panel module performance in the form of thesingle-diode equivalent circuit. The Five Parameters method isreliable in predicting the energy produced by the solar panels whenthe input data is limited. The results for using the Five Parametersin monocrystalline solar panels were Isc = 1.827 A, Imp = 0.662 A,Voc = 18.221 V, Vmp = 15.019 V, Pmp = 9.955 W. And the results inpolycrystalline solar panels were Isc = 1.926 A, Imp = 0.686 A, Voc =17.594 V, Vmp = 14.166 V, Pmp = 9.722 W. Based on the results; itwas concluded that the most efficient and optimised types of solarpanels on natural conditions in Sendang Biru Beach was themonocrystalline solar panel because it produced electrical outputpower of 9.955 W. Therefore, there could be a manufacturer ofsolar energy power plants to reduce the cost of electricity in thecoastal area, such as in Sendang Biru Beach.

Power Optimization of Electric Developments in Diesel Power Plant for the Electrical Energy Sources using Dynamic Programming Algorithm

The electricity need in the G4 Building at the State University ofMalang was more than 85 kVA. All electrical devices could beactivated; but when the energy source was inactive, all electricityrequirements were transferred to the diesel power plant (DPP).However, the electrical capacity of DPP was only 20 kVA;therefore, it was necessary to optimize the electrical power load sothat the DPP energy could be absorbed optimally using the roomscheduling and electrical devices priority systems. The DynamicProgramming Algorithm was embedded in the power optimizationsystem to help optimize the work. The power optimization prototypewas used to simulate the 1st floor of the G4 Building’s condition.The system consisted of a controller, a central controller, and auser interface. the controller comprised of a current sensor,microcontroller, and a relay. The central controller consisted ofRaspberry Pi 3 hardware that was installed as the server to answerthe HTTP request from the controller and user interface. The userinterface was displayed in a dynamic web to ease the user inmanaging the electrical devices and entering the room usageschedule. The power optimization system managed the electricalenergy from DPP by turning on the electrical devices according tothe priority value. The power optimization system tests were dividedinto six problems, of which each stage had an error value of 0%.

Load Impact Analysis Towards Power Loss in Distribution Substation in Wlingi District

This research aimed to find: (1) the distribution substations configuration in Kesamben Feeder, Wlingi District, (2) how much was the loading in those distribution substations, (3) how much load imbalance in the distribution substation’s load, and (4) how much was the power loss towards the imbalance load. This research used descriptive analysis by analyzing the loading imbalance towards the power loss of distribution substation in one feeder. The results showed that the higher percentage of loading imbalance meant higher power loss. However, although an imbalance percentage was more significant than a smaller percentage, the power loss that occurred might be more substantial due to the probable higher loading percentage so that the power loss in the substation was also influenced by the loading value, apart from the load imbalance.

Implementation of Gyrinops Versteegii Gaharu Leaves as a Dye-Sensitized Solar Cell

Dye-Sensitized Solar Cell (DSSC) is a photoelectrochemical solarcell that uses electrolytes as the cargo transport medium. Gratzeldeveloped it as an alternative resource through the discovery of thelatest solar cell material by mimicking the photosynthesis processcalled photo-electrochemical reactions. According to the researchof Saputra, flavonoids can be used as dyes in Dye-Sensitized SolarCells, while Yanti in 2014 studied the agarwood leaf extract thatcontained flavonoids and chlorophyll. This study aimed to design,build, and test Dye-Sensitized Solar Cell by testing the lightabsorption, and the Performance of Dye-Sensitized Solar Cell usingAgarwood Chlorophyll. This research extracted the Gyrinopsversteegii that was grouped into young, medium and old leaves.With the same dose of extract, 15 grams of agarwood leaves weredissolved in 96% ethanol for 100 ml. The results showed that eventhough the maximum absorption power was the same, or 4.00, themedium leaves absorbed the light more than its wavelength range.The DSSC performance test results obtained the voltages of theyoung, medium, and old agarwood leaves that were 0.398 V, 0.399V, and 0.369 V. The currents of those leaves were 0.01 mA, 0.01mA, and 0.01 mA respectively.