CD Skripsi

Prakiraan Beban Listrik Jangka Pendek Kota Pekanbaru Berdasarkan Data Beban Histori Dan Temperatur

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Temperature changing has affected to the electrical load consumption. It has considered in the calculation of short-term load forecasting. In this study, ANFIS method was used to forecast short-term load using historical data of electrical load and temperature. From the testing process, the MAPE value has obtained during the procces for daily bunch from Monday to Sunday and Public Holiday is included, i.e. 8.567%; 5.013%; 5.341%; 4.214%; 7.741%; 6.635%; 6.875% and 0.022689%, respectively. The addicting of temperature data buffering has proven that forecasting accuracy is increased. The best membership function was Generalized Bell (GBellMF) rather than the other membership functions. Keywords : Load forecasting, Short-term load forecasting, Artificial Neural Network, Fuzzy-Inference, ANFIS, MATLAB, ANFIS toolbox.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

07 04. 117 (0049)

Penerbit

Pekanbaru : Universitas Riau – Fakultas Teknik – Elektro., 2017

Deskripsi Fisik

xxiii, 124 hlm.; ill.; 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

07 04. 117 (0049)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

ELEKTRO

Info Detail Spesifik

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Pernyataan Tanggungjawab

DAUS

Versi lain/terkait

Lampiran Berkas

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