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ITS » Undergraduate Theses » Teknik Fisika S1
Posted by tondoindra@gmail.com at 29/11/2011 13:37:19  •  1726 Views


WIND ENERGY POTENTIAL MODELLING AND MAPPING USING ARTIFICIAL NEURAL NETWORK ON KARANGKATES DAM AT MALANG CITY

Author :
ZAKARIA, AHMAD ZAKI  ( 2406100057 )




ABSTRAK

Angin merupakan fenomena fisis cuaca yang tidak bias dipisahkan dalam kehidupan kita sehari-hari. Angin juga merupakan sumber energi yang tidak akan pernah habis. Fenomena terjadinya angin dapat dipengaruhi oleh beberapa variable lain diantaranya suhu udara tekanan udara dan kelembaban udara. Pada tugas akhir ini akan membahas tentang pemodelan kecepatan dan arah angin menggunakan metode jaringan syaraf tiruan JST dengan menggunakan variable-variabel yang berpengaruh suhu udara tekanan udara dan kelembabab udara. Metode JST yang digunakan adalah metode training Lavenberg Marquardt. Dari proses training yang dilakukan didapatkan RMSE training kecepatan angin sebesar 0.0669 dan nilai RMSE training untuk arah angin sebesar 01061. Untuk nilai VAF training kecepatan angin sebesar 77.8375 dan nilai VAF training arah angin sebesar 81.0271. Selain itu kecepatan dan arah angin akan dipetakan menggunakan windrose sehingga pola distribusi kecepatan dan arah angin di bendungan Karangkates dapat terlihat. Dari hasil windrose yang telah didapatkan selanjutnya aka dibandingkan antara windrose dari data asli yang didapatkan dari stasiun dengan windrose data hasil dari pemodelan dan terjadi perbedaan pada arah angin dikarenakan model tidak sepenuhnya mengikuti pola dari data asli yang didapatkan dari stasiun.


ABSTRACT

Wind is an inseparable physic phenomenon from our daily life. Wind also one of energy source that will never ran out. Wind occurrence could be depending on several other variable such as air temperature air pressure and air humidity. This final project will discuss about how to make a model of wind velocity an wind direction using artificial neural network. Training method of this artificial neural network in this project in using Lavenberg Marquardt method. From the training process it can be determined RMSE value of wind velocity training is 0.0669 and RMSE value of wind direction training is 01061. The VAF value of wind velocity training is 77.8375 and VAF value of wind direction training is 81.0271. Moreover wind velocity and wind direction will be mapped using windrose model so wind velocity and wind direction distribution in Karangkates dam can be determined. From the windrose that have been made it will be compared between the windrose that made from genuine data and windrose that made from model data and from the result it appeared that there was difference between the two of them. It caused by the data model is not fully-following the genuine data got from the station.



Keywordskecepatan angin;arah angin; jaringan syaraf tiruan; windrose.
 
Subject:  Jaringan saraf (ilmu komputer)
Contributor
  1. IMAM ABADI, ST.MT
  2. Ir. ALI MUSYAFA, MT
Date Create: 21/02/2011
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Undergraduate-3100011042998
Collection ID: 3100011042998
Call Number: RSF 006.32 Zak p


Source
Undergraduate Thesis,Physics Engineering ,RSF 006.32 Zak p, 2011

Coverage
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Rights
Copyright @2011 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




[ Download - Open Access ]

  1.  ITS-Undergraduate-16343-2406100057-abstract-idpdf.pdf - 188 KB
  2.  ITS-Undergraduate-16343-2406100057-abstract-enpdf.pdf - 188 KB
  3.  ITS-Undergraduate-16343-2406100057-conclusionpdf.pdf - 209 KB
  4.  ITS-Undergraduate-16343-2406100057-paperpdf.pdf - 540 KB




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