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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) REKAYASA DINAMIKA Jurnal Ilmiah Teknik Mesin Seminar Nasional Informatika (SEMNASIF) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Otomasi Kontrol dan Instrumentasi KACANEGARA Jurnal Pengabdian pada Masyarakat JISTech (Journal of Islamic Science and Technology) JURNAL PENDIDIKAN TAMBUSAI Informatik : Jurnal Ilmu Komputer DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Journal of Robotics and Control (JRC) JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Jurnal Abdidas INSANtek – Jurnal Inovasi dan Sains Teknik Elektro Tedc Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Jurnal Multidisipliner Kapalamada Jurnal Polimesin The Indonesian Journal of Computer Science Jurnal ISO: Jurnal Ilmu Sosial, Politik dan Humaniora
Yuliadi Erdani, Yuliadi
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Journal : Journal of Robotics and Control (JRC)

 1 
Design and Implementation of Artificial Neural Networks to Predict Wind Directions on Controlling Yaw of Wind Turbine Prototype Dzulfikri, Zaky; Nuryanti, Nuryanti; Erdani, Yuliadi
Journal of Robotics and Control (JRC) Vol 1, No 1 (2020): January
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.1105

Abstract

Wind  energy as one of the new renewable energies has an important role in replacing fossil energy sources in Indonesia. In order to make the wind turbine's performance more efficient in extracting energy from the wind, it is necessary to control the actuation movements pitch and yaw of the wind turbine horizontal. Controlling the actuator yaw can increase the absorption efficiency of the power to the rotor face toward the direction of the wind. The purpose of this thesis is to be able to predict the direction of the coming wind, then move the turbine rotor in the predicted direction. In this final project a wind turbine prototype is used with a precision of 5.3%, then for the data acquisition section, a wind direction sensor is built to change the amount of wind direction to a quantity that can be measured in units of degrees, and anemometer to measure wind speed. In making the wind direction prediction algorithm, artificial neural network (ANN) method is used with input parameters such as wind speed, temperature, humidity, pressure, and altitude. Data acquisition is done at one minute intervals with long data collection for one day, 1072 data are obtained, the data is then fed to the ANN model that has been prepared. Based on the results of tests that have been done, it is found that the Mean Absolute Error in the model is 0.4%.
Design and Implementation of Artificial Neural Networks to Predict Wind Directions on Controlling Yaw of Wind Turbine Prototype Zaky Dzulfikri; Nuryanti Nuryanti; Yuliadi Erdani
Journal of Robotics and Control (JRC) Vol 1, No 1 (2020): January
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.1105

Abstract

Wind  energy as one of the new renewable energies has an important role in replacing fossil energy sources in Indonesia. In order to make the wind turbine's performance more efficient in extracting energy from the wind, it is necessary to control the actuation movements pitch and yaw of the wind turbine horizontal. Controlling the actuator yaw can increase the absorption efficiency of the power to the rotor face toward the direction of the wind. The purpose of this thesis is to be able to predict the direction of the coming wind, then move the turbine rotor in the predicted direction. In this final project a wind turbine prototype is used with a precision of 5.3%, then for the data acquisition section, a wind direction sensor is built to change the amount of wind direction to a quantity that can be measured in units of degrees, and anemometer to measure wind speed. In making the wind direction prediction algorithm, artificial neural network (ANN) method is used with input parameters such as wind speed, temperature, humidity, pressure, and altitude. Data acquisition is done at one minute intervals with long data collection for one day, 1072 data are obtained, the data is then fed to the ANN model that has been prepared. Based on the results of tests that have been done, it is found that the Mean Absolute Error in the model is 0.4%.
Co-Authors Abdul jalil Abdur Rohman Harits Martawireja Abdur Rohman Harits Martawireja Abyanuddin Salam Adhikara Firdaus Adhitya Sumardi Sunarya Aisyah, Aulia Alief Sugata Alvian Reihan Anugrah, Mochammad Dimas Arbiyan Saputra Asep Deni Mulyadi Athoriq, Alif Yasir Bhawana Mulia, Sandy Budiyarto, Aris Candra, Wahyu Adhie Daffa Hamdany Darwis, Mardis Dede Sujana Doni Viana Dzulfikri, Zaky Eka Suaib, Eka Fachry Abda El Rahman Fadhli Rizqi Fadzkal Mayzanio Fahrurozi, Ahmad Farhan, Abiyyu Fatana, Ahmad Feliks Eldad Larobu Fitria Suryatini Gumadi, Riki Adiwijaya Hanifah, Anna Hendy Rudiansyah Hendy Rudiansyah Hidayatullah, Cecep Taufiq Ijazilah, Aqila Bihar Indrajaya, Nathan Ismail Rokhim Jody Jovantio Kamsudin La Ode Muh. Fathur Rachim La Ode Muhamad Fathur Rachim Laode Abdul Gamsir Lestary, Igni Lubis, Abrar Wahid Luthfia Najmi Rachmadiyanti Majid, Fauzan Maulana , Gun Gun Mochammad Rizky Febrian Mohammad Fauzi Muhammad Defval Andika Saripudin Muhammad Dzaki Muhammad Hamzah Nur Fadhilah Muhammad Rausyanfikry Hablillah Muhammad Yusuf Naufal Shoyifful Mubarok Naufal, Mochammad Nur Jamiludin Nuryanti Nuryanti Nuryanti Nuryanti Pagiling, luther Permata, Nia Nuryanti Purnomo, Wahyudi Putra, Fachrizal Cesar Putra, Muhammad Idris Putri Amelia Kresna Rachim, La Ode Muhamad Fathur Rachim, Muhamad Fathur Raden Muhammad Nafish Ginanjar Raden Rinova Sisworo Ramdani, Muhammad Reffi Fachrushidieq Alfian Ridwan Rizqi Aji Pratama Rizqi Aji Pratama Rujhan Milah Salim Setiawan Sambas, Achmad Sandy Bhawana Mulia Sarosa Castrena Abadi Setyawan Ajie Sukarno Simanjuntak, Raja Agung Hasudungan Sita Khoerunnisa Siti Aminah Siti Aminah SUBEKTI, RUMINTO Suhada, Muhammad Giri Sunarya, Adhitya Sumardi Susilawati, Fera Tri Syamdesta Ataullah Tovani, Ivan Tryantama, Naufal Wahyu Adi Chandra Zaky Dzulfikri  La Ode Abdul Jalil