EMAIL: PASSWORD:
Front Office
UPT. PERPUSTAKAAN
Institut Teknologi Sepuluh Nopember Surabaya


Kampus ITS Sukolilo - Surabaya 60111

Phone : 031-5921733 , 5923623
Fax : 031-5937774
E-mail : libits@its.ac.id
Website : http://library.its.ac.id

Support (Customer Service) :
timit_perpus@its.ac.id




Welcome..guys!

Have a problem with your access?
Please, contact our technical support below:
LIVE SUPPORT


Moh. Fandika Aqsa


Davi Wahyuni


Tondo Indra Nyata


Anis Wulandari


Ansi Aflacha




ITS » Master Theses » Teknik Elektro - Telematika S2
Posted by dee@its.ac.id at 13/11/2014 17:15:41  •  980 Views


KLASIFIKASI POLA DINAMIS POWER SWITCH DENGAN HYBRID POWER SYSTEM BERBASIS BACKPROPAGATION NEURAL NETWORK

POWER SWITCH DYNAMIC PATTERN LASSIFICATION WITH HYBRID POWER SYSTEM BASE ON BACKPROPAGATION NEURAL

Author :
PERDANA, RIDHO HENDRA YOGA ( 2212206004 )




ABSTRAK

Konsumsi energi konvensional seperti pembakaran bahan bakar fosil memainkan peran penting dalam isu pemanasan global. Karbon dioksida metana nitrous oxide dll menyebabkan efek rumah kaca cenderung menciptakan perubahan iklim. Dalam situasi ini energi terbarukan diperlukan untuk mengurangi konsumsi energi konvensional. Penelitian ini menyajikan sebuah Intelligent Switch untuk menggabungkan kedua sumber daya energi. Teknik kecerdasan buatan Backpropagation Neural Network BPNN dirancang untuk mengklasifikasi dan mengontrol aliran energi yang didistribusikan secara dinamis berdasarkan pembangkit energi terbarukan. Hasil dari penelitian ini adalah mengklasifikasikan pola dinamis power switch untuk dua tipe solar panel. Pengujian pertama untuk solar panel 60 watt didapatkan simpangan baku pelatihan sebesar 07 dan simpangan baku pengujian sebesar 028. Pengujian kedua untuk solar panel 900 watt didapatkan simpangan baku pelatihan sebesar 005 dan simpangan baku pengujian 018. Akurasi yang didapat menggunakan metode ini mencapai 83. Pada penelitian ini juga dirancang prototipe Intelligent switch dengan solar panel yang dipasang pada sebuah rumah kecil.


ABSTRACT

Conventional energy consumption such as burning fossil fuels plays an important role in the global warming issue. Carbon dioxide methane nitrous oxide etc. cause the green house effect tended to create the climate changing. In this situation the renewable energy is necessary to reduce the conventional energy consumption. This research proposes an intelligence switch to combine both energy resources. The intelligence technique BackPropagation Neural Network BPNN is designed to classify and control the distributed energy flow dynamically based on renewable energy generation. The results of this research is to classify a dynamic pattern of the power of power switches with two different types of solar panels. The first test for solar panel 60 watt obtained training standart deviation of 0.7 and a standart deviation of test is 0.28. The second test of 900 watt solar panels to obtain training standart deviation of 0.5 and 0.18 for testing. Accuracy obtained using this metod reaches 83. This research also designed a prototype of the intelligence switch for solar cells installed in a small house.



KeywordsIntelligent Switch; Backpropagation; Neural network; Classify
 
Subject:  Tenaga listrik, Sistem
Contributor
  1. Prof. DR. Ir. Mauridhi Hery P, M. Eng
  2. DR. Ardyono Priyadi, ST., M. Eng
Date Create: 20/01/2014
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Master-22103140000864
Collection ID: 22103140000864
Call Number: RTE 621.312 136 Per k


Source
Master Thesis of Electrical Engineering, RTE 621.312 136 Per k, 2014

Coverage
ITS Community

Rights
Copyright @2014 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-Master-33617-2212206004-abstract_id.pdf - 197 KB
  2.  ITS-Master-33617-2212206004-abstract_en.pdf - 197 KB
  3.  ITS-Master-33617-2212206004-conclusion.pdf - 369 KB




 Similar Document...




! ATTENTION !

To facilitate the activation process, please fill out the member application form correctly and completely

Registration activation of our members will process up to max 24 hours (confirm by email). Please wait patiently

POLLING

Bagaimana pendapat Anda tentang layanan repository kami ?

Bagus Sekali
Baik
Biasa
Jelek
Mengecewakan





You are connected from 18.206.194.83
using CCBot/2.0 (https://commoncrawl.org/faq/)



Copyright © ITS Library 2006 - 2019 - All rights reserved.
Dublin Core Metadata Initiative and OpenArchives Compatible
Developed by Hassan