HASAN HIDAYATULLAH, RAMA (2022) PERAMALAN BEBAN LISTRIK JANGKA PENDEK MENGGUNAKAN OPELM (OPTIMALLY PRUNED EXTREME LEARNING MACHINE) PADA SISTEM KELISTRIKAN CILEGON, BANTEN. S1 thesis, UNIVERSITAS SULTAN AGENG TIRTAYASA.
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Abstract
Short-term forecasting of electrical load is a very important factor in the planning and operation of electric power systems. The purpose of forecasting the electricity load is so that the demand for electricity and electricity supply can be balanced. Load characteristics in the Cilegon region are so volatile that the OPELM (Optimally Pruned Extreme Learning Machine) method was used to forecast electrical loads. The advantages of OPELM are in the fast learning speed and selection of the right model even though the data has a non linear pattern. The accuracy of the OPELM method can be known using actual data. The accuracy criteria used is MAPE (Mean Absolute Percent Error). The average error of the minimum forecasting test results showed MAPE of 2.1252%.
| Item Type: | Thesis (S1) | |||||||||
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| Additional Information: | Peramalan beban listrik jangka pendek merupakan faktor yang sangat penting dalam perencanaan dan pengoperasian sistem tenaga listrik. Tujuan dari peramalan beban listrik adalah agar permintaan listrik dan penyediaan listrik dapat seimbang. Karakteristik beban di wilayah Cilegon sangat fluktuatif sehingga pada penelitian ini digunakan metode OPELM (Optimally Pruned Extreme Learning Machine)untuk meramalkan beban listrik. Kelebihan OPELM ada pada learning speed yang cepat dan pemilihan model yang tepat meskipun datanya mempunyai pola tidak linier. Keakuratan metode OPELM dapat diketahui dengan menggunakan data aktual. Kriteria keakuratan yang digunakan adalah MAPE (Mean Absolute Percent Error). Error rata-rata hasil pengujian peramalan paling minimum menunjukkan MAPE sebesar 2,1252%. | |||||||||
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | |||||||||
| Divisions: | 03-Fakultas Teknik 03-Fakultas Teknik > 20201-Jurusan Teknik Elektro |
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| Depositing User: | Rama Hasan Hidayatullah | |||||||||
| Date Deposited: | 21 Jun 2023 15:11 | |||||||||
| Last Modified: | 21 Jun 2023 15:11 | |||||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/15837 |
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