MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic
Maximum Power Point Tracking is a method to track power point of an energy source in order to generate maximum power. One of the MPPT method for photovoltaic system is fractional open voltage MPPT. In this paper the fractional open voltage MPPT is modified by using artificial neural network trained...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Departement of Electrical Engineering, Faculty of Engineering, Universitas Brawijaya
2014-12-01
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| Series: | Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) |
| Online Access: | https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/259 |
| _version_ | 1797640005114396672 |
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| author | Gunawan Wibisono Sholeh Hadi Pramono Muhammad Aziz Muslim |
| author_facet | Gunawan Wibisono Sholeh Hadi Pramono Muhammad Aziz Muslim |
| author_sort | Gunawan Wibisono |
| collection | DOAJ |
| description | Maximum Power Point Tracking is a method to track power point of an energy source in order to generate maximum power. One of the MPPT method for photovoltaic system is fractional open voltage MPPT. In this paper the fractional open voltage MPPT is modified by using artificial neural network trained using genetic algorithm. Artificial neural networks are successfully trained by using genetic algorithm. The best mean squared error (MSE) value obtained is 0.000453. The network tested using test data, yielding average error = 0.00949509 and MSE = 0.00012814. The neural network-based MPPT can improve the fractional open voltage MPPT by 4.79%.
Index Terms---Genetic Algorithm, MPPT, Neural Network, Photovoltaic |
| first_indexed | 2024-03-11T13:25:42Z |
| format | Article |
| id | doaj.art-b88cb032ebbe4468be697db82f6d4780 |
| institution | Directory Open Access Journal |
| issn | 2460-8122 |
| language | English |
| last_indexed | 2024-03-11T13:25:42Z |
| publishDate | 2014-12-01 |
| publisher | Departement of Electrical Engineering, Faculty of Engineering, Universitas Brawijaya |
| record_format | Article |
| series | Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) |
| spelling | doaj.art-b88cb032ebbe4468be697db82f6d47802023-11-03T07:20:29ZengDepartement of Electrical Engineering, Faculty of Engineering, Universitas BrawijayaJurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems)2460-81222014-12-018218118610.21776/jeeccis.v8i2.259149MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem PhotovoltaicGunawan Wibisono0Sholeh Hadi Pramono1Muhammad Aziz Muslim2Program Magister Teknik Elektro Fakultas Teknik, Universitas BrawijayaJurusan Teknik Elektro Fakultas Teknik Universitas BrawijayaJurusan Teknik Elektro Fakultas Teknik Universitas BrawijayaMaximum Power Point Tracking is a method to track power point of an energy source in order to generate maximum power. One of the MPPT method for photovoltaic system is fractional open voltage MPPT. In this paper the fractional open voltage MPPT is modified by using artificial neural network trained using genetic algorithm. Artificial neural networks are successfully trained by using genetic algorithm. The best mean squared error (MSE) value obtained is 0.000453. The network tested using test data, yielding average error = 0.00949509 and MSE = 0.00012814. The neural network-based MPPT can improve the fractional open voltage MPPT by 4.79%. Index Terms---Genetic Algorithm, MPPT, Neural Network, Photovoltaichttps://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/259 |
| spellingShingle | Gunawan Wibisono Sholeh Hadi Pramono Muhammad Aziz Muslim MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) |
| title | MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic |
| title_full | MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic |
| title_fullStr | MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic |
| title_full_unstemmed | MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic |
| title_short | MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic |
| title_sort | mppt menggunakan metode hibrid jst dan algoritma genetika untuk sistem photovoltaic |
| url | https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/259 |
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