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Advisor(s)
Abstract(s)
This paper describes recent work on the development of a wireless-based remote monitoring system for household energy
consumption and generation in Madeira Island, Portugal. It contains three different main sections: (1) a monitoring system
for consumed and produced energy of residencies equipped with photovoltaic (PV) systems, (2) developing a tool to
predict the electricity production, (3) and proposing a solution to detect the PV system malfunctions. With the later tool, the
user (owner) or the energy management system can monitor its own PV system and make an efficient schedule use of
electricity at the consumption side. In addition, currently, the owners of PV systems are notified about a failure in the
system only when they receive the bill, whereas using the proposed method conveniently would notify owners prior to bill
issue. The artificial neural network was employed as a tool together with the hardware-based monitoring system which
allows a daily analysis of the performance of the system. The comparison of the predicted value of the produced electricity
with the actual production for each day shows the validity of the method.
Description
Keywords
Roof-top PV system Prediction Artificial neural network Monitoring system . Faculdade de Ciências Exatas e da Engenharia
Citation
Torabi, R., Rodrigues, S., Cafôfo, N., Pereira, L., Quintal, F., Nunes, N., & Morgado-Dias, F. (2020). A global monitoring system for electricity consumption and production of household roof-top PV systems in Madeira. Neural Computing and Applications, 32(20), 15835-15844. https://doi.org/10.1007/s00521-018-3832-3
Publisher
Springer