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Penerapan On Grid Photovoltaic pada Mesin Pembuat Pakan Udang untuk Mengurangi Biaya Operasional Kelompok Ternak Udang Glagah, Lamongan Pamuji, Feby Agung; Riawan, Dedet Candra; Soedibyo, Soedibyo; Suryoatmojo, Heri; Ashari, Mochamad
Sewagati Vol 8 No 3 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i3.805

Abstract

Indonesia merupakan salah satu negara produsen udang terbesar di duina. Udang merupakan salah satu komoditas perikanan andalan Indonesia yang sangat potensial untuk diekspor. Sebagai salah satu komoditas unggulan nasional udang selalu menjadi pilihan untuk bisa dilibatkan dalam upaya peningkatan pendapat negara dan menggapai target kenaikan produksi hingga 250% pada tahun 2024 mendatang. Jawa Timur menempati urutan ketiga dengan produksi udang terbanyak. Salah satu daerah di Jawa Timur yang aktif memproduksi udang adalah Kabupaten Lamongan, tepatnya di Kecamatan Glagah. Biaya pakan udang tidaklah murah sehingga banyak peternak udang yang mengeluhkan besarnya pengeluaran mereka untuk membeli pakan udang. Oleh karena itu dirancanglah inovasi mesin pembuat pakan udang bertenaga sinar matahari. Pada sistem ini, alat pembuat pakan udang akan dioperasikan menggunakan listrik bertenaga matahari. Listrik yang dihasilkan oleh panel surya dapat menghemat pengeluaran listrik untuk operasi mesin pembuat pakan udang ini. Penggunaan panel surya juga dapat mendukung akselerasi penggunaan energi baru terbarukan guna mewujudkan energi yang bersih dan murah di kalangan masyarakat. Inovasi alat ini bertujuan untuk mengenalkan kepada masyarakat mengenai penerapan energi baru terbarukan di bidang peternakan, membantu peternak untuk mandiri dalam penyediaan pakan, dan dapat mengurangi biaya pengeluaran para peternak di daerah Glagah Lamongan. Kegiatan abmas ini sudah berhasil terlaksana dan alat inovasi kami berhasil di terapkan. Alat inovasi kami berdampak kepada penurunan biaya pakan udang di daerah Glagah Lamongan.
Novel hybrid of marine predator algorithm-Aquila optimizer for droop control in DC microgrid Aribowo, Widi; Suryoatmojo, Heri; Pamuji, Feby Agung
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp3703-3715

Abstract

This study presents a hybrid method, namely the marine predator algorithm (MPA) and Aquila optimizer (AO). The proposed algorithm is named MAO. AO duplicated the existence of the Aquila bird in nature while hunting for prey while MPA was inspired by predators in marine animal life. Although AO is widely accepted, it has several disadvantages. This causes various weaknesses such as a weak exploitation phase and slow growth of the convergence curve. Thus, certain exploitation and exploration in conventional AO can be studied to achieve the best balance. The MPA demonstrates the capacity to deliver optimal design and statistically efficient outcomes. The proposed method used AO as the main algorithm. To measure the performance of the proposed method, this study depicted a comparison using the AO, MPA, and whale optimization algorithm (WOA) methods. This paper was evaluated the performance of MAO on twenty-one CEC2017 benchmark functions test and droop control performance on direct current (DC) microgrid. From the simulation, MAO shows superior convergence ability. The proposed method and its application to droop control was successfully implemented and implied a promising performance.
Design And Simulation Of 10 kW BLDC Motor Speed Control For Electric Vehicles Using FOC Based On Fuzzy Logic Control Rizqulloh, Mochamad Shofwan; Pamuji, Feby Agung; Suryoatmojo, Heri
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 1 (2024): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i1.386

Abstract

The use of electric vehicles in the current era has begun to spread evenly. Apart from the issue of air pollution produced by ICE vehicles, the ease and practicality of using electric vehicles is the reason why the public is starting to become interested in electric vehicles. Electric vehicle manufacturers are currently choosing BLDC motors for their production vehicles because they are considered suitable for applications that require high power and torque output. However, BLDC motors require more complicated control techniques than other DC motors. The commonly used BLDC motor speed control methods are trapezoidal scalar control and field oriented control. FOC is a type of BLDC motor control with a vector control method which has advantages in terms of efficiency compared to scalar control methods. Many studies on implementing FOC as speed control for BLDC motors, but the research that has been carried out still uses PI control as a basis, where it is known that PI control has shortcomings in the form of complexity in its design. Fuzzy Logic Control is known to be easy to design and reliable in control, so this paper will show the performance of Fuzzy-PI based FOC control as speed control for 10kW BLDC motor in simulation using Simulink program. The simulation results of proposed Fuzzy-PI based FOC method have better response than PI based FOC in terms of starting response with 6.43 times faster rise time, 2.45 times faster settling time, 96.31% lower overshoot value and reliability in overcoming disturbances up to 78.05% lower overshoot value and 2.33 times faster recovery time.
Comprehensive Calculation of Vanadium Redox Flow Battery Capacity For 5kW Lighting Applications Nadilah Laksmi Marahaini; Feby Agung Pamuji; Vita Lystaningrum Budiharto Putri
International Journal of Marine Engineering Innovation and Research Vol 9, No 4 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v9i4.22160

Abstract

Vanadium Redox Flow Batteries (VRFB) have emerged as a potential solution for renewable energy storage due to their scalability and long lifetime. However, optimizing their operational efficiency and addressing the issue of parameter accuracy for the right load pose significant challenges. This paper aims to quantify the critical parameters of VRFBs and analyze their performance in powering the system under various flow rate operating conditions. Simulations are performed using MATLAB software and unit blocks to evaluate the behavior of VRFBs during discharge and charge conditions at three electrolyte flow rates: 10, 5, and 1 liter per minute (lpm). The analysis focuses on key parameters, including operating duration, charge/discharge time, and state of charge. The results show that higher flow rates increase the discharge duration, while lower flow rates lead to shorter operating times and more pronounced ripples caused by pump control instability and electrolyte density variations. Therefore, designing appropriate parameters in VRFB systems is critical to developing sustainable energy storage solutions and supporting the implementation of clean energy technologies.
Power Allocation based on ANN for Hybrid Battery and Supercapacitor Storage System in EV Rahmawan, Hanif Adi; Lystianingrum, Vita; Adityanugraha, Dimas Febry; Pamuji, Feby Agung
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 2 (2024): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i2.385

Abstract

The paper focuses on presented an ArtificialNeural Network (ANN) approach to allocate power for a hybridenergy storage system (HESS) in an Electric Vehicle (EV). TheHESS is comprised of a battery and supercapacitor, and theANN algorithm aims to optimize power allocation between thesetwo energy storage devices. The data for ANN training wasbased on cost optimization-based power allocation fromprevious research. While optimization can often take highcomputational resource and time, it is expected that a welltrained ANN can allocate power for the EV HESS more quickly.In this research, the inputs to the ANN are the required powerderived from the drive cycle, energy and power capacity of thebattery and supercapacitor, and state of charge (SoC) of thebattery and supercapacitor. The trained ANN was trained withvarious inputs not used in the training and it shows satisfactoryperformance.
Sizing of Energy Storage Systems in Electric Vehicles based on Battery-Supercapacitor Technology Alfani, Denny; Adityanugraha, Dimas Febry; Putri, Vita Lystianingrum Budiharto; Pamuji, Feby Agung
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 2 (2024): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i2.388

Abstract

The purpose of this research is to determine the ideal hybrid energy storage system (HESS) size with the goal to improve the effectiveness and efficiency of combined battery and supercapacitor energy storage in electric vehicles. The research uses Mixed Integer Linear Programming (MILP) to determine the most suitable configurations using simulation data from a modeled electric vehicle. The results show that MILP works at identifying the specific capacity needs of the storage system, which change based on the vehicle's power and energy capacity. The innovation provides a paradigm for the development of sustainable and highly efficient electric vehicles in the future, while also enhancing the functionality of current electric vehicles.
Design and Simulation Control Speed of Brushless DC 7 HP Using Direct Torque Method with Ripple Suppression Pamuji, Feby Agung; Rayhan, Muhammad Faris; Soedibyo; Yurisqi, Muhammad Athariq; Suryoatmojo, Heri; Arumsari, Nurvita
MEIN : Journal of Mechanical, Electrical & Industrial Technology Vol. 1 No. 1 (2024): MEIN : Journal of Mechanical, Electrical & Industrial Technology
Publisher : P3M Politeknik Perkapalan Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35991/mein.v1i1.13

Abstract

The last decade, electric cars have grown so rapidly. One of the driving parts in electric cars is the Brushless DC Motor (BLDC). The use of BLDC motors is needed because this motor has low mechanical losses, this is because the motor does not use brushes. However, in operation, there is still a ripple that is complained by the control or drive of the motor so that the efficiency of the motor rotation output torque and speed is not perfect. One way to operate a BLDC motor is by direct torque control method. The Direct Torque Control method became popular for controlling BLDC motors because it provides a fast dynamic torque response, the variables controlled in this DTC are flux and torque. Direct torque control (DTC) is a method used to control torque and speed on a motor with a variable frequency drive (VFD). This method is a calculation that includes estimating motor flux and torque based on the voltage and current on the stator. In the stator, the flux is estimated based on the stator voltage while the torque is estimated from the stator flux estimator and motor current.The input values measured to the DTC control are the current and voltage of the motor. The torque output of this DTC has a fairly high ripple along with the application of a larger load so that changes in motor load affect ωr. Ripple Torque that affects the speed of the rotor must be given an additional circuit, namely Ripple Suppression. This additional circuit will suppress the ripple so that the torque and speed rotation of the BLDC motor will be better. Therefore, this research will discuss the design and simula tion of the BLDC motor using the direct torque control method with ripple suppression which is expected to produce more efficient output from the BLDC motor due to the torque ripples on the motor have been reduced by the ripple suppression circuit. From the research results, it can be seen that the efficiency of BLDC motors increases by 2 to 3 percent at starting time and increases by around 1.5 percent at steady state.