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ITS » Paper and Presentation » Sistem Tenaga - S2
Posted by aprill@is.its.ac.id at 25/01/2013 08:51:59  •  1894 Views


INVERTER-PV SYSTEM DESIGN WITH ARTIFICIAL NEURAL NETWORKS FOR ACTIVE AND REACTIVE POWER INJECTION

Author :
HERMAWAN, ADITYA CHANDRA ( 2209201009 )




ABSTRAK

Pendekatan umum pada pembangkitan tenaga listrik adalah dengan menempatkan suatu plant sentral yang mendistribusikan listrik pada jaringan transmisi dan distribusi. Penelitian ini dilakukan untuk mendesain dan mensimulasikan modul photovoltaic PV yang dicoupling dengan modul mppt berupa boost converter dan modul injeksi daya aktif dan reaktif berupa voltage source inverter yang pada akhirnya terhubung pada grid utility yaitu jaring distribusi PLN. Modul Photovoltaic umumnya digunakan untuk memenuhi keperluan daya aktif baik itu pada jaringan ataupun pada modul beban elektrik yang terhubung pada grid utility. Desain Inverter dan Konverter Boost pada penelitian ini digunakan untuk dapat mengatur daya aktif dan daya reaktif yang masuk menuju grid. Kontrol MPPT dari Konverter Boost akan dikendalikan menggunakan Artificial Neural Network ANN dan injeksi daya aktif dan reaktif pada grid akan diregulasi melalui inverter sumber tegangan dikendalikan mengunakan ANN dengan referensi daya dari Photovoltaic. Hasil simulasi menunjukkan Modul Photovoltaic mencapai daya optimal pada irradiasi 1000 Wm2 dan suhu 35 oC PV sebesar 1.24 kW dengan efisiensi sistem PV-Inverter memiliki akurasi output daya yang tinggi mencapai 9997 untuk output daya 1168192 Watt dengan akurasi daya reaktif mencapai 99 . Performansi respon perubahan daya terhadap Irradiance juga relatif cepat dengan rentan waktu 0023 detik terhadap perubahan daya Inverter baik itu aktif P ataupun reaktif Q. Sistem juga mampu mempertahankan kondisi faktor daya pada grid mendekati 09 dengan perubahan irradiance dari 1000 Wm2 500 Wm2 lalu menuju 900 Wm2 dengan waktu steady rata rata antar tenggang waktu perubahan kurang dari 014 detik.


ABSTRACT

The most common method of power generation are generally achieved by dispatching a central plant which was used to distribute electricity throughout transmission and distribution network. This research was conducted to design and simulate a PV module coupled with MPPT boost converter and Inverter Power Injection Module which later are connected to the Utility Grid. Photovoltaic module generally were used as an active power source for electric networks or Local load that connected to the grid as a standalone module. The main idea of this research was to propose inverter and boost converter design that may be used as a power regulator for active and reactive power which connected to the grid. The proposed controller are Artificial Neural Network ANN that control the injection of active and reactive power with Photovoltaic PV power as the reference. The simulation result concluded that PV module were able to produce optimum peak power on irradiance of 1000 Wm2 and temperature of 35 oC. With maximum power capacities of 124 kW the system efficiency was noted 9997 for power output of 1168192 Watt with reactive power accuracy of 99. The performance of system response against Irradiance change was relatively fast within transition time of 0023 secon of active P and Reactive Q power output. This system also capble of maintain the power factor of utility grid close to 09 with irradiance changes from 1000 Wm2 500 Wm2 to 900 Wm2 with average steady time between changes less than 014 secon.



KeywordsPhotovoltaic; Voltage Source Inverter; Boost Converter; ANN
 
Subject:  Sistem kekuatan tenaga surya
Contributor
  1. Prof. Dr. Ir. Mochamad Ashari, M.Eng.
  2. Heri Suryoatmojo, ST., MT., Ph.D
Date Create: 25/01/2013
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-paper-13021130001905
Collection ID: 13021130001905
Call Number: RTE 621.312 44 Her d


Source
Paper and Presentation, Electrical Engineering, RTE 621.312 44 Her d, 2013

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Copyright @2012 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




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