RANCANG BANGUN PEMANTAUAN PEMAKAIAN ENERGI LISTRIK MENGGUNAKAN LABVIEW
Abstract
In conventional electric measurement devices, measurements are made on the use of electrical energy as a whole whereconsumers can only see information on the results of the use of electrical energy by looking at the total powerconsumption 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 tomeasure, monitor and store data quickly and accurately. With this tool will be realized a design system monitoring theuse of electrical energy in real time through the computer instead of kWH meter analog or digital. This concept is one ofthe energy management solutions that enable consumers to obtain statistical data on electrical energy consumption indetail. 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.References
Hutoro Koko (2015), “Desain Smart Meter Untuk Memantau Dan Identifikasi Pemakaian Energi Listrik Pada Sektor
Rumah Tangga Menggunakan Backpropagation Neural Networkâ€. ITS Surabaya.
J. Uteley, and L. Shorrock (2008), “Domestic Energy Fact File 2008â€, Technical Report for Building Research
Establishment : Garston, UK.
K.E Martinez, K.A Donelly, and J.A Laitner (2010), “Advanced Metering Initiatives and Residential Feedback
Programs: A Meta-Review for Households Electricity-Saving Opportunitiesâ€, Technical Report E105 for
American Council for an Energy-Efficient Economy (ACEE), USA.
Energy Consumption in United Kingdom, Technical Report for Department of Energy & Climate Change (2010),
London.
G. W. Hart (1992), “Nonintrusive Appliance Load Monitoringâ€, Proceedings IEEE, Vol. 80, No. 12.
J. G. Roos, I. E. Lane, E. C. Lane, and G. P. Hanche (1994), “Using neural networks for non-intrusive monitoring of
industrial electrical loads,†in Proceedings of IEEE Instrumentation and Measurement Technology Conference.
Jian Liang, Simon K. K. Ng, Gail Kendall, and John W. M. Cheng (2010),†Load Signature Study—Part I: Basic
Concept, Structure, and Methodology,†IEEE Transactions On Power Delivery, Vol 25.
Kusumadewi, S (2004), â€Membangun Jaringan Syaraf Tiruan Menggunakan MATLAB & EXCEL LINKâ€, Graha Ilmu.
Purnomo, M.H, dan Kurniawan, A (2006), “Supervised Neural Networks dan Aplikasinyaâ€, Graha Ilmu
C. Laughman, K. Lee, R. Cox, S. Shaw, S. B. Leeb, L. Norford, and P. Armstrong (2003), “Power Signature Analysisâ€.
IEEE Power & Energy Magazine.
Y.Y Hong, and J.H Chou (2012), “Nonintrusive Energy Monitoring for Microgrids Using Hybrid Self-Organizing
Feature-Mapping Networks,†Energies, 2012.