Desain Maximum Power Point Tracking Pada Turbin Angin Permanent Magnet Synchronous Generator (PMSG) 1500 Watt Dengan Pitch Dan Voltage Control Berbasis Artificial Neural Network (ANN)

Azmi, Muhammad Ulil (2021) Desain Maximum Power Point Tracking Pada Turbin Angin Permanent Magnet Synchronous Generator (PMSG) 1500 Watt Dengan Pitch Dan Voltage Control Berbasis Artificial Neural Network (ANN). Undergraduate thesis, InstitutTeknologi Sepuluh Nopember.

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Abstract

Tugas akhir ini berisi desain MPPT pada sebuah turbin angin PMSG dengan pitch dan voltage controller menggunakan ANN. Terdapat tiga permodelan yakni, (1) pengaturan berbasis ANN dengan menggunakan pitch control, (2) menggunakan voltage controller, dan (3) menggunakan kombinasi pitch dan voltage controller sekaligus. Pemodelan dengan MATLAB sebagai sarana pembuatan ANN dan simulasi. Input ANN pitch angle controller adalah Cpopt dan λ dengan output βref, pada ANN voltage controller ialah Vwind dan Vact dengan keluaran duty cycle. Simulasi dibuat dalam empat keadaan yakni pada kecepatan naik dan turun pada daerah operasi 2, dan 3 turbin angin. Hasil yang diperoleh menunjukkan turbin angin dengan pitch controller memiliki efisiensi 53,4-53,7% meningkat-menurun pada daerah 2 dan 62,8%-66,2% dan dapat membatasi keluaran pada daerah 3. Turbin angin dengan voltage controller memiliki efisiensi 93,4-97% dan mencapai daya maksimum akan tetapi mengalami ripple dan lonjakan pada daerah 2 dan tidak membaasi keluaran pada daerah operasi 3. Sedangkan pada turbin dengan pitch and voltage controller memiliki efisiensi 93,4-97% meningkat-menurun dengan ripple dan lonjakan perubahan pada daerah 2 dan dapat membatasi keluaran pada daerah operasi 3 dengan efisiensi energi 94,6%-94,2% meningkat-menurun dan juga dapat mencapai daya maksimum. ====================================================================================================== This final project contains the MPPT design on a PMSG wind turbine with a pitch and voltage controller using ANN. There are 3 models in this research, ANN-based settings with only pitch control , only voltage controllers , and with both pitch and voltage controllers. Modeling is done using MATLAB software as tool for making ANN and simulation. The architecture of the ANN pitch/voltage controller is an ANN with 2 inputs, 2 hidden layers with 20 and 10 neurons and 1 output layer with 1 neuron and 1 output. The ANN input in pitch angle controller are Cpopt and λ with βref as output , voltage controller input are Vwind and Vact with duty cycle as output. Simulations are made in 4 conditions, increasing and decreasing speed in region 2 and 3 of wind turbines. The results are, wind turbine model with pitch controller has an efficiency of 62,8%-66,2% in region 2 and 53,4-53,7% and able to limit the output in region 3, in voltage controller only the system has 93,4-97% efficiency with ripple and spike and reach maximum power in region 2 but can not limit the output in region 3, and turbine with pitch and voltage controller has an efficiency of 93,4-97% with ripple and spike in region 2 and can limit the output in region 3 with efficiency 94,6%-94,2% whilst attaining maximum power altogether.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: MPPT, Turbin Angin, Pitch Control, Voltage Control, ANN, Wind Turbine.
Subjects: Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
T Technology > TJ Mechanical engineering and machinery > TJ828 Wind turbines
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001 Production of electric energy or power
Divisions: Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User: Muhammad Ulil 'Azmi
Date Deposited: 23 Feb 2021 12:20
Last Modified: 24 Feb 2021 02:29
URI: https://repository.its.ac.id/id/eprint/82717

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