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Erschienen in: Neural Computing and Applications 20/2020

13.11.2018 | Advances in Bio-Inspired Intelligent Systems

A global monitoring system for electricity consumption and production of household roof-top PV systems in Madeira

verfasst von: Roham Torabi, Sandy Rodrigues, Nuno Cafôfo, Lucas Pereira, Filipe Quintal, Nuno Nunes, Fernando Morgado-Dias

Erschienen in: Neural Computing and Applications | Ausgabe 20/2020

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Abstract

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.

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Metadaten
Titel
A global monitoring system for electricity consumption and production of household roof-top PV systems in Madeira
verfasst von
Roham Torabi
Sandy Rodrigues
Nuno Cafôfo
Lucas Pereira
Filipe Quintal
Nuno Nunes
Fernando Morgado-Dias
Publikationsdatum
13.11.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 20/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3832-3

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