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ITS » Master Theses » Sistem Tenaga - S2
Posted by anisw@its.ac.id at 24/05/2016 09:25:25  •  1068 Views


DESAIN SMART METER UNTUK MEMANTAU DAN IDENTIFIKASI PEMAKAIAN ENERGI LISTRIK PADA SEKTOR RUMAH TANGGA MENGGUNAKAN BACKPROPAGATION NEURAL NETWORK

SMART METER DESIGN TO MONITOR AND IDENTIFY ELECTRICAL ENERGY CONSUMPTION IN HOUSEHOLD SECTOR USING BACKPROPAGATION NEURAL NETWORK

Author :
HUTORO, KOKO  ( 2212201201 )




ABSTRAK

Penelitian ini mengusulkan sebuah konsep smart meter sebagai pengganti kWH meter. Smart meter merupakan salah satu solusi manajemen energi yang memungkinkan konsumen untuk memperoleh data statistik konsumsi energi listrik secara terperinci. Smart meter yang didesain memiliki fitur-fitur yang dapat memantau arus beban mengidentifikasi peralatan-peralatan elektronika dan mencatat pemakaian energi listrik secara aktual meliputi waktu penggunaan peralatan elektronika serta menampilkan biaya yang harus dibayarkan oleh konsumen. Fiturfitur tersebut tidak dimiliki oleh kWH meter analog dan digital. Dalam proses perancangan smart meter menggunakan piranti sensor arus ACS712 sebagai pengganti transformator arus. Alasan pemilihan sensor arus ACS712 adalah untuk meminimalkan fenomena distorsi dalam pengukuran arus dari transformator arus. Hasil eksperimen dan simulasi diperoleh untuk memvalidasi metodologi dan untuk menunjukkan beberapa manfaat yang dapat dicapai dengan pengenalan smart meter yang diaplikasikan pada sektor rumah tangga dalam konteks identifikasi profil beban secara real time menggunakan metode backpropagation neural network. Dari metode yang diusulkan diperoleh hasil signifikan yaitu akurasi identifikasi beban yang mencapai 99.


ABSTRACT

This research proposes a concept of smart meters as a replacement of kWh meters. Smart meters are one of the energy management solutions that allow consumers to obtain statistical data of electrical energy consumption in detail. Smart meters are designed to have features that can monitor the load current identify electronic equipment and record the actual electrical energy consumption include the use of electronic equipment and the time to show the cost to be paid by the consumer. These features are not owned by the kWh meter analog and digital. In the design process using smart meters ACS712 current sensor devices as a substitute for the current transformer. The reason ACS712 current sensor selection is to minimize the distortion phenomenon in the current measurement of the current transformer. Experimental and simulation results obtained to validate the methodology and to demonstrate some benefits that can be achieved with the introduction of smart meters are applied to the household sector in the context of the identification load profile in real time using backpropagation neural network method. Of the proposed method obtained significant results that identification load accuracy reaches 99.



KeywordsSmart Meter; Manajemen Energi; Identifikasi Profil beban; Backpropagation Neural Network
 
Subject:  NONE
Contributor
  1. Prof. Dr. Ir. Adi Soeprijanto, MT
  2. Prof. Ir. Ontoseno Penangsang, M.Sc, Ph.D
Date Create: 22/01/2015
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Master-22103160001649
Collection ID: 22103160001649
Call Number: RTE 621.387 8 Hut d


Source
Master Theses of Electrical Engineering, RTE 621.387 8 Hut d, 2015

Coverage
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Rights
Copyright @2015 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-41592-2212201201-abstract-inpdf.pdf - 291 KB
  2.  ITS-Master-41592-2212201201-abstract-enpdf.pdf - 253 KB
  3.  ITS-Master-41592-2212201201-conclusionpdf.pdf - 251 KB




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