Implementasi Labview Untuk Pemantauan Pemakaian Energi Listrik

DOI: https://doi.org/10.21070/jeee-u.v2i1.1321

Author (s)


(1) * Muhammad Yusuf Yunus   (State Polytechnic of Ujung Pandang)  
        Indonesia
(2)  Marhatang Marhatang   (State Polytechnic of Ujung Pandang)  
        Indonesia
(*) Corresponding Author

Abstract


In conventional electric measurement devices, measurements are made on the use of electrical energy as a whole where consumers can only see information on the results of the use of electrical energy by looking at the total power consumption amount indicated on the meter kWh meter. Based on the above problems, the author aims to raise the title "Design of Monitoring System of Electricity Energy Usage using LabVIEW". The LabVIEW program has the ability to measure, monitor and store data quickly and accurately. With this tool will be realized a design system monitoring the use of electrical energy in real time through the computer instead of kWH meter analog or digital. This concept is one of the energy management solutions that enable consumers to obtain statistical data on electrical energy consumption in detail. From the results of monitoring the use of loads, obtained very good results in monitoring the usage of energy, which in this case using household burden.



Keywords

LabView, ACS712, Current, Monitoring



Full Text: PDF



References


[1] H. Koko, "Desain Smart Meter Untuk Memantau Dan Identifikasi Pemakaian Energi Listrik Pada Sektor Rumah Tangga Menggunakan Backpropagation Neural Network," ITS Surabaya, 2015.

[2] S. Suryaningsih, "RANCANG BANGUN ALAT PEMANTAU PENGGUNAAN ENERGI LISTRIK RUMAH TANGGA BERBASIS INTERNET," presented at the SEMINAR NASIONAL FISIKA 2016 UNJ, 2016.

[3] I. D. Utomo, "PROSES PENGAMBILAN DATA ENERGI (KWH) METER ELEKTRONIK PADA GARDUINDUK 150 KV PT. PLN (PERSERO) P3BJB REGION JAWA TENGAH DAN DIY UNITPELAYANAN TRANSMISI SEMARANG," presented at the Makalah Seminar Kerja Praktek, 2012.

[4] I. Ismujianto and I. Isdawimah, "DESAIN AKUISISI DATA KUALITAS DAYA LISTRIK," Poli-Teknologi, vol. 15, 2017.

[5] J. Roos, I. Lane, E. Botha, and G. P. Hancke, "Using neural networks for non-intrusive monitoring of industrial electrical loads," in Instrumentation and Measurement Technology Conference, 1994. IMTC/94. Conference Proceedings. 10th Anniversary. Advanced Technologies in I & M., 1994 IEEE, 1994, pp. 1115-1118.

[6] Y.-Y. Hong and J.-H. Chou, "Nonintrusive energy monitoring for microgrids using hybrid self-organizing feature-mapping networks," Energies, vol. 5, pp. 2578-2593, 2012.


Article View

Abstract views : 69 times | PDF files viewed : 99 times

Dimensions, PlumX, and Google Scholar Metrics

10.21070/jeee-u.v2i1.1321


Refbacks

  • There are currently no refbacks.




Copyright (c) 2018 JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA)

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.