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A Relational Conceptual Model in GIS for the Management of Photovoltaic Systems

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  • Fabio Piccinini

    (Dipartimento di Ingegneria Civile Edile e dell’Architettura, Università Politecnica delle Marche, 60131 Ancona, Italy)

  • Roberto Pierdicca

    (Dipartimento di Ingegneria Civile Edile e dell’Architettura, Università Politecnica delle Marche, 60131 Ancona, Italy)

  • Eva Savina Malinverni

    (Dipartimento di Ingegneria Civile Edile e dell’Architettura, Università Politecnica delle Marche, 60131 Ancona, Italy)

Abstract

The aim of this manuscript is to define an operational pipeline of work, from data acquisition to the report creation, for the smart management of PV plants. To achieve such an ambitious result, we exploit the implementation of a conceptual model, deployed through a relational database to retrieve any kind of information related to the PV plant. The motivation that drove this research is due to the increasing construction of PV plants. In fact, following European and international investments that heavily stimulated the use of clean energy, the need to maintain PV plants in their maximum efficiency for their whole lifecycle emerged, to bring about benefits from both the ecological and the economic points of view. While the research community focuses on finding new and automatic ways to detect faults automatically, few efforts have been made considering the so-called Operation and Maintenance (O&M). A relational conceptual model may facilitate the management of heterogeneous sources of information, which are common in complex PV plants. The purpose of the present study is to provide companies and insiders with a GIS-based tool to maintain the energy efficiency of a PV plant. Indeed, it is a common practice used by companies dealing with O&M of PV plants to create technical reports about the health status of the plants. This operation, made manually, is very time consuming and error prone. To overcome this latter drawback, this work attempts to encourage the use of GIS in the PV plants O&M, which proves to be efficient to deal with fault management and to assure a good level of energy production. The developed conceptual model, tested on two real case studies, proved to be complete, cost-effective and efficient to be replicated in other existing plants.

Suggested Citation

  • Fabio Piccinini & Roberto Pierdicca & Eva Savina Malinverni, 2020. "A Relational Conceptual Model in GIS for the Management of Photovoltaic Systems," Energies, MDPI, vol. 13(11), pages 1-21, June.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2860-:d:367010
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    References listed on IDEAS

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    1. Roberto Pierdicca & Marina Paolanti & Andrea Felicetti & Fabio Piccinini & Primo Zingaretti, 2020. "Automatic Faults Detection of Photovoltaic Farms: solAIr, a Deep Learning-Based System for Thermal Images," Energies, MDPI, vol. 13(24), pages 1-17, December.

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