Artificial neural network for real time modelling of photovoltaic system under partial shading

Maria Carla Di Vincenzo

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

8 Citations (Scopus)

Abstract

Shading caused by surrounding objects is an important issue for solar energy system design and analysis. In the special case of building integrated photovoltaic (BIPV) systems, the prediction of the partial shading is critical in order to reduce losses due to poor Maximum Power Point Tracking (MPPT). This paper will present a technique that uses Artificial Neural Network to predict the output power from a photovoltaic array in case of partial shading.
Original languageEnglish
Title of host publication2010 IEEE International Conference on Sustainable Energy Technologies (ICSET)
Place of PublicationNew York
PublisherIEEE
Number of pages5
ISBN (Print)9781424471928
DOIs
Publication statusPublished - Dec 2010
EventSustainable Energy Technologies (ICSET) IEEE International Conference - , United Kingdom
Duration: 13 Dec 2010 → …

Conference

ConferenceSustainable Energy Technologies (ICSET) IEEE International Conference
CountryUnited Kingdom
Period13/12/10 → …

Keywords

  • artificial neural network
  • real time modelling
  • photovoltaic system
  • partial shading

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  • Cite this

    Di Vincenzo, M. C. (2010). Artificial neural network for real time modelling of photovoltaic system under partial shading. In 2010 IEEE International Conference on Sustainable Energy Technologies (ICSET) IEEE. https://doi.org/10.1109/ICSET.2010.5684464