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All Journal International Journal of Electrical and Computer Engineering Perfecting a Video Game with Game Metrics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) TEKNOLOGIA Journal of Robotics and Control (JRC) IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science I-Com : Indonesian Community Journal
Muhammad Abdillah
Universitas Pertamina
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Design of spark ignition engine speed control using bat algorithm Herlambang Setiadi; Karl O. Jones; Teguh Aryo Nugroho; Muhammad Abdillah; Herri Trilaksana; Tahta Amrillah
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp794-801

Abstract

The most common problem in spark ignition engine is how to increase the speed performance. Commonly researchers used traditional mathematical approaches for designing speed controller of spark ignition engine. However, this solution may not be sufficient. Hence, it is important to design the speed controller using smart methods. This paper proposes a method for designing speed controller of a spark ignition engine using the bat algorithm (BA). The simulation is carried out using the MATLAB/SIMULINK environment. Time domain simulation is carried out to investigate the efficacy of the proposed method. From the simulation results, it is found that by designing speed controller of spark ignition engine using PI based bat algorithm, the speed performance of spark ignition engine can be enhanced both in no load condition and load condition compared to conventional PI controler.
Improvement of voltage profile for large scale power system using soft computing approach Muhammad Abdillah; Herlambang Setiadi; Danang Sulistyo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.13379

Abstract

In modern power system operation and planning, reactive power is an important part of power system operation to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to reduce the total power loss of the transmission line and improve the voltage stability of the system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. To examine the efficacy of the proposed algorithm, Java-Madura-Bali (JAMALI) 500kV power system grid is used as the test system. From the simulation results, the use of PSO and ABC algorithms to obtain the sizing of the capacitor’s capacity can reduce the power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
Smart DIPSS for Dynamic Stability Enchancement on Multi-Machine Power System Herlambang Setiadi; Fakhruddin Arrazi; Muhammad Abdillah; Awan Uji Krismanto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 1: March 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i1.3429

Abstract

Disruption of the electric power system always results in instability. These disturbances can be in the form of network breaks (transients) or load changes (dynamic). Changes in load that occur suddenly and periodically cannot be responded well by the generator so that it can affect the dynamic stability of the system. This causes the occurrence of frequency oscillations in the generator. A poor response can cause frequency oscillations for a long period. This will result in a reduction in the available power transfer power. In a multi-machine power system, all the machines work in synchrony, so the generator must operate at the same frequency. Therefore, disturbances that arise will have a direct impact on changes in electrical power. In addition, changes in electrical power will have an impact on mechanical power. The difference in response speed between a fast electrical power response and a slower mechanical power response will result in instability. As a result of these differences, the system oscillates. The addition of the excitation circuit gain is less able to stabilize the system. To solve the problem, additional signal changes are required. The additional signal is generated by the Dual Input Power System Stabilizer (DIPSS) setting using the Ant Colony Optimization (ACO) method.Disruption of the electric power system always results in instability. These disturbances can be in the form of network breaks (transients) or load changes (dynamic). Changes in load that occur suddenly and periodically cannot be responded well by the generator so that it can affect the dynamic stability of the system. This causes the occurrence of frequency oscillations in the generator. A poor response can cause frequency oscillations for a long period. This will result in a reduction in the available power transfer power. In a multi-machine power system, all the machines work in synchrony, so the generator must operate at the same frequency. Therefore, disturbances that arise will have a direct impact on changes in electrical power. In addition, changes in electrical power will have an impact on mechanical power. The difference in response speed between a fast electrical power response and a slower mechanical power response will result in instability. As a result of these differences, the system oscillates. The addition of the excitation circuit gain is less able to stabilize the system. To solve the problem, additional signal changes are required. The additional signal is generated by the Dual Input Power System Stabilizer (DIPSS) setting using the Ant Colony Optimization (ACO) method.
LQR Tuning Using AIS for Frequency Oscillation Damping Muhammad Abdillah; Teguh Aryo Nugroho; Herlambang Setiadi
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 4 (2019): Desember 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.51192

Abstract

Commonly, primary control, i.e. governor, in the generation unit had been employed to stabilize the change of frequency due to the change of electrical load during system operation. But, the drawback of the primary control was it could not return the frequency to its nominal value when the disturbance was occurred. Thus, the aim of the primary control was only stabilizing the frequency to reach its new value after there were load changes. Therefore, the LQR control is employed as a supplementary control called Load Frequency Control (LFC) to restore and keep the frequency on its nominal value after load changes occurred on the power system grid. However, since the LQR control parameters were commonly adjusted based on classical or Trial-Error Method (TEM), it was incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios. To overcome this problem, this paper proposed an Artificial Immune System (AIS) via clonal selection to automatically adjust the weighting matrices, Q and R, of LQR related to various system operating conditions changes. The efficacy of the proposed control scheme was tested on a two-area power system network. The obtained simulation results have shown that the proposed method could reduce the settling time and the overshoot of frequency oscillation, which is better than conventional LQR optimal control and without LQR optimal control.
KLASIFIKASI BEBAN LISTRIK DENGAN MACHINE LEARNING MENGGUNAKAN METODE K-NEAREST NEIGHBOR Salma Salma; Favian Dewanta; Muhammad Abdillah
RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Vol 5, No 2 (2022): RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer)
Publisher : Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/resistor.5.2.163-172

Abstract

ABSTRAKSistem pengenalan beban listrik merupakan peran yang penting dalam melakukan manajemen dan penghematan listrik. Sistem pengenalan beban listrik memiliki keandalan dalam memperoleh informasi yang relevan dari setiap beban listrik. Pada penelitian ini, akan dilakukan analisis karakteristik berbagai fitur beban listrik secara independen dan hubungan pencocokan antara fitur yang berbeda dan algoritma klasifikasi yang berbeda. Yaitu dengan melakukan perbandingan antara dua algoritma klasifikasi K-Nearest Neighbours dan Regresi Logistik Multinomial dari segi akurasi dan kecepatan proses dalam analisis. Sistem klasifikasi akan mengidentifikasikan jenis, model, dan prasyarat yang tidak diketahui dari beban listrik dan mengelompokannya. Karakteristik kelistrikan dari beban listrik yang akan diteliti antaralain besarnya tegangan dan arus root mean square, gelombang harmonisa, daya dan faktor daya dari variasi sample beban listrik yang berbeda. Hasil penelitian pada metode k-Nearest Neighbours didapatkan akurasi sebesar 99.619% sedangkan dengan metode Regresi Logistik Multinomial didapatkan akurasi sebesar 91.125% Kata Kunci : Beban Listrik, Klasifikasi, K-Nearest Neighbours, Regresi Logistik MultinomialABSTRACTThe electrical load recognition system plays an important role in managing and saving electricity. In this study, the caharacteristic of various electrical load features in independent condition and the matching relationship between different features and different classification algorithm will be analyzed by doing a comparison between two classification algorithms, k-Nearest Neighbours and Multinomial Logistic Regression in terms of accuracy and speed of analysis process. The classification system will be identify unknown types, models and prerequisites of different electrical loads and classify them. The characteristics of the electrical load that will be analyzed include the magnitude of root mean square voltage and current, harmonic waves, power series, and power factor from variety of different electrical load samples. The results of the research on the k-Nearest Neighbors method obtained an accuracy of 99.619% while the Multinomial Logistics Regression method obtained an accuracy of 91.125%.Keywords: Electrical Load, Classification, Machine Learning, k-Nearest Neighbours, Multinomial Logistic Regression
MODEL SMART ENERGY METER SEBAGAI MONITORING SYSTEM BERBASIS INTERNET OF THINGS DALAM PEREKAMAN DAN PERAMALAN KONSUMSI LISTRIK Muhammad Abdillah
JURNAL TEKNOLOGIA Vol 5 No 1 (2022): Jurnal Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The electricity monitoring system that implemented by PLN currently still uses conventional technology, so that requires officers to record energy usage manually and periodically from house to house. Seeing these conditions, authors wants to take the great potential of this problem. Smart energy meters are designed to automatically record electricity consumption and estimate costs to be paid, so that electricity usage can be controlled in real time. The components used are NodeMCU ESP8266 as a data processor, PZEM-004T as a current and voltage measuring sensor while calculating the energy used in a certain time, RTC DS1307 as a time module, LCD2004 as a display, SD card module as a data storage backup, push buttons as accessibility switching modes, and power supply as a power supply. In delivering data, the website is used as a user-friendly interface media. There also additional features that predict the power and cost that will use by user in the future. The forecasting uses the Encoder-Decoder Long Short-Term Memory (LSTM) Neural Network method. This smart energy meter prototype has high accuracy. Measurements show results similar to energy calculations on PLN meters, with an error percentage of 0.032%. In addition, the forecasting feature also has accurate results. Shown by the RMSE value of 0.49 and MAPE of 4%.
Advanced virtual inertia control against wind power intermittency Muhammad Abdillah; Syailendra Andi; Teguh Aryo Nugroho; Herlambang Setiadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1256-1265

Abstract

Rapid industrial development requires more energy to support their manufacturing processes. Unfortunately, conventional energy was mostly utilized as a primary energy source which is unfriendly to nature and can damage the environment. Nowadays, the transformation from the use of conventional energy to renewable energy sources is increasingly being socialized throughout the world. However, the existence of renewable energy poses new challenges in the world of electricity systems where their effect is reducing the inertia (inertialess) value of conventional energy such as thermal generators. This condition causes frequency oscillations and leads to blackout the electricity system. To overcome this problem, this paper proposed advanced virtual inertia control (VIC) based on an superconducting magnetic energy storage (SMES) employed to accommodate the effects of the integration of renewable energy into the electric power system. SMES was choosen because it has a fast response and an efficiency rate of up to 90%. A two-area power system model was utilized to examine the proposed VIC model based on SMES. From the simulation results, VIC based on has succeeded in reducing frequency oscillations by compressing the system overshoot and reducing the settling time to steady-state.
Retired electric vehicle battery to reduce the load frequency control oscillation in the micro grid system Muhammad Abdillah; Rozan Haqi Pratama; Nita Indriani Pertiwi; Herlambang Setiadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1266-1275

Abstract

The potential of a retired electric vehicle battery (REVB) is its capacity to provide backup power supply to the power system grid. This paper proposed energy storage system (ESS) based on REVB called retired battery energy storage system (retired BESS) to tackle the intermittent of renewable energy source such as wind turbine and dynamic load change. To examine the efficacy of the proposed technique, the load frequency control (LFC) of microgrid (MG) system is utilized in this study and the proposed technique is compared to conventional LFC controller, PI controllers, superconducting magnetic energy storage (SMES), and a new electric vehicle battery. The kind of retired BESS cell used in this study is Li-ion nickel manganese cobalt oxide (NMC) type with a state of charge as of 70%. The capacity of each cell for retired BESS is 38 Ah. From the simulation result, the use of retired BESS can reduce frequency oscillation, compress the settling time to reach steady state, and maintain the robustness of the MG system. A retired BESS has a minimum error performance index value compared to conventional LFC, proportional integral (PI) controller, and SMES.
Design intelligent maximum power point tracking for photovoltaic at Universitas Airlangga Herlambang Setiadi; Firdaus Bima Firmansyah; Prisma Megantoro; Tahta Amrillah; Herri Trilaksana; Galih Bangga; Muhammad Abdillah; Awan Uji Krismanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1212-1222

Abstract

Rooftop photovoltaic (PV) plant is one ot the independent electricity that us favorable in recent year. Rooftop PV plant can be used as the source of smart building as well as fast charging station. Although rooftop PV plant could provide clean and sustainable energy from solar, they also come with disadvantages in term of intermittent power output. This intermittent power output is due to the uncertainty of the source. To tackle this problem, maximum power point tracking method is essential. Maximum power point tracking (MPPT) method can be used to extract maximum power from the solar cell in all conditions. This paper proposes an intelligent method for designing DC-DC MPPT based on fruit fly optimization (FFO) on realistic rooftop PV plant. Practical rooftop PV plant in Universitas Airlangga is employed as the testing system. The proposed method's efficacy is evaluated using time domain simulation. According to the simulation results, the proposed method can significantly extract power from PV.
Design of photovoltaic system for public school building Muhammad Abdillah; Fathan Mujahid Satria; Nita Indriani Pertiwi; Herlambang Setiadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp56-65

Abstract

The increase in energy needs to support sustainable development will trigger a large additional power supply. Unfortunately, a current energy source is mostly produced by fossil fuels. This condition can affect the increase of global warming and climate change. Nowadays, many countries including Indonesia are aware of the effect of the use of fossil fuels on environmental devastation. Therefore, the use of clean energy gets more attention from many countries since its energy source is unlimited and harvested from nature. One of the clean energy sources that are widely utilized over the world is photovoltaic (PV). PV is an appropriate clean energy technology to be utilized in Indonesia since this country lies on the equator line and gets solar irradiance over the year. This paper proposed the design of PV systems for a public-school building. These PV schemes proposed in this study are classified into off-grid, on-grid, and hybrid PV systems. From the simulation results, it is shown that the hybrid PV system with energy supplied by PT. PLN (State Electricity Company) results in the highest saving annual cost and provides an environmentally friendly energy source for public-school buildings.
Co-Authors Afif, Yusrizal Awan Uji Krismanto Danang Sulistyo Fakhruddin Arrazi Fathan Mujahid Satria Favian Dewanta Firdaus Bima Firmansyah Galih Bangga Herlambang Setiadi Herlambang Setiadi Herlambang Setiadi Herlambang Setiadi Herminarto Nugroho Herri Trilaksana Karl O. Jones Marza Ikhsan Marzuki Muhammad Nita Indriani Pertiwi Prayogi, Soni Prisma Megantoro R Harry Arjadi Ramon Zamora Rezi Delfianti Rozan Haqi Pratama Salma Salma Syailendra Andi Tahta Amrillah Teguh Aryo Nugroho Teuku Muhammad Roffi Tirta Jayadiharja Wahyu Agung Pramudito Wahyu Kunto Wibowo