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2018 | OriginalPaper | Chapter

11. Application of Neural Networks to Validate the Power Generation of BIPVS

Authors : Andrés Julián Aristizábal Cardona, Carlos Arturo Páez Chica, Daniel Hernán Ospina Barragán

Published in: Building-Integrated Photovoltaic Systems (BIPVS)

Publisher: Springer International Publishing

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Abstract

Since the BIPVS offers the possibility to replace part of the traditional building materials, with a possible price reduction, in comparison to a classic rooftop installation [1, 2], then the correct estimation of system level performances, system reliability and system availability is becoming more important and popular among installers, integrators, investors and owners; with that purpose several tools and models were developed [3–5]. The combination of different phenomena, such as solar radiation available on site, dust presence, shadowing or UV radiation over long outdoor exposure, affect in different ways the real performance of BIPV systems and thus the related economic evaluations [6–8].

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previous chapter Behavior and Analysis of the Power System in Steady State

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Title: Application of Neural Networks to Validate the Power Generation of BIPVS
Authors: Andrés Julián Aristizábal Cardona
Carlos Arturo Páez Chica
Daniel Hernán Ospina Barragán
Publisher: Springer International Publishing
Book: Building-Integrated Photovoltaic Systems (BIPVS)
Print ISBN: 978-3-319-71930-6

Electronic ISBN: 978-3-319-71931-3

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-71931-3_11

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