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All Journal ASEAN Journal of Systems Engineering MEDIA ELEKTRIKA PROSIDING CSGTEIS 2013 Jurnal Teknologi Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) IJITEE (International Journal of Information Technology and Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Mokhammad Isnaeni Bambang Setyonegoro
Jurusan Teknik Elektro Dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Peningkatan Stabilitas Transien pada Turbin Angin Berbasis DFIG Menggunakan SFCL tipe Bridge Doane Puri Mustika; Sasongko Pramono Hadi; Mokhammad Isnaeni B; Mohd. Brado Frasetyo; Tumiran
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 4: November 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v11i4.5031

Abstract

Today’s electrical energy is mainly produced by burning fossil fuels, which actually has negative effects on earth, namely global warming. In the electricity sector, measures that can be taken to reduce emissions include replacing conventional generators with renewable ones. Wind energy is one type of new renewable energies (NREs) with the potential to reduce emissions. Wind turbines widely used today are variable speed wind turbines, such as the doubly-fed induction generator (DFIG). DFIG has numerous advantages, like having more flexibility and being able to control both active and reactive powers. However, it often encounters instability problems in its system when experiencing transients. Therefore, a solution that can improve transient stability in DFIG is needed. The bridge-type superconducting fault current limiter (SFCL) was used in this research as a solution to improve the transient stability in DFIG, which consisted of two diodes and two inductors. This bridge-type SFCL operates by limiting the current in the event of faults, preventing the system from voltage drops or trips. The simulation results were analyzed under two circumstances. In the first circumstance, the 9 MW DFIG wind turbine system which was given faults using SFCL produced a voltage value of 219 V, with a more stable frequency value of 50 Hz, and an active power value of 9 MW. Meanwhile, when a system that did not use SFCL was given faults, the voltage dropped from the normal state of 219 V to 100 V. The frequency value was less stable, fluctuating between 49.75 Hz and 50.25 Hz, while the active power dropped from 9 MW to 6 MW. This result proves that the bridge-type SFCL method effectively increases the transient stability in DFIG.
Penetrasi Fotovoltaik dengan Metode MILP dan Pertimbangan Pembebanan Minimal Teknis Alfi Bahar; Muhammad Yasirroni; Sarjiya; M. Isnaeni Bambang Setyonegoro
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i1.4531

Abstract

Technological development and the reduction of installation costs have caused a rapid growth of solar power plants in Indonesia. The National Electricity Company (Perusahaan Listrik Negara, PLN) strives to achieve the energy mix of renewable energy to 23% by 2025. Solar power plants are unique in that they only supply their power during the daytime. It makes solar power plants connected to the power system change the load profile of the Java-Bali system. In this study, the penetration of solar power plants changed the scheduling of the Java-Bali system because the penetration was installed to the technical minimum loading of existing power plants. When penetration is too big, thermal generator scheduling failure is possible. Unit commitment and economic dispatch with mixed-integer linear programming (MILP) method using CPLEX and Python were carried out to calculate the fuel and generation costs per kWh before and after the penetration. MILP was used to solve the cost fuel equation, namely an integer and nonlinear mix equations, that are challenging to be solved using standar nonlinear programming methods. Due to the use of the MILP-UC, all objective function equations and restraint functions must be linear functions. The tests were conducted for three years, from 2023 to 2025. Simulation results on the Java-Bali system show that the capacity of solar power plants penetrating the Java-Bali system against the peak load will be 52%, 52%, and 50% in 2023, 2024, and 2025, respectively. Meanwhile, penetration of solar power plants to technical minimum loading of existing power plants resulted in the fuel cost falling by 23% in 2023 and 22% in 2024 and 2025. Lastly, the cost of generation per kWh will be decreased by 8% in 2023 and will be as low as 7% in 2024 and 2025.
Prakiraan Beban Listrik Menggunakan Metode Jaringan Saraf Tiruan dengan Data yang Terbatas Elang Bayu Trikora; Sasongko Pramonohadi; M. Isnaeni Bambang Setyonegoro
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 3: Agustus 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i3.6437

Abstract

As time changes, electric load demand forecasting is one of the vital things in generation and distribution planning. Various ways can be implemented in forecasting electrical energy demands, one of which is by using the artificial neural network method, which is a method that mimics the ability of the human brain to receive an input and then carry out processing between the neurons within to produce information based on the processes that occur within the neurons. This research uses a neural network method to forecast the electric load in Jayawijaya Regency. This research builds a neural network architecture suitable to the data obtained from National Electricity Company (Perusahaan Listrik Negara, PT PLN Indonesia) UP 3 Wamena to find an architecture model suitable with high accuracy. Due to the limited data owned to forecast electric load, an interpolation method based on the owned original data was carried out to increase the amount of the existing data. In this way, more data can be used as input, allowing the model to forecast load requirements more accurately. These propagated data were used as input data in the artificial neural network model. After conducting iterative testing using a neural network, it is found that the model that fitted the data was feed-forward long short-term memory (LSTM) network, this model can obtain errors in accordance with the standards of a model to perform forecasts of 0.04% with nine epochs.
Co-Authors - Hardiansyah Adhi Susanto Alfi Bahar Anak Agung Gede Sugianthara Doane Puri Mustika Eka Firmansyah Eka Firmansyah Elang Bayu Trikora Fransisco Danang Wijaya Haneef Nouval Alannibras Humaidi Hardiansyah Hardiansyah Maemonah, Maemonah Mahalla Mahalla - Mahalla, Mahalla Maimun - Mohd. Brado Frasetyo Mr Suharyanto, Mr Mrs Fitrizawati, Mrs Muhammad Yasirroni Mursyidah - Rian Fatah M. Sarjiya Sasongko Pramono Hadi Suharyanto Suharyanto Tumiran Yusuf Susilo Wijoyo