Numerical Modelling and Digitalization Analysis for a Photovoltaic Pumping System Placed in the South of Romania

Laurentiu Fara, Dan Craciunescu and Silvian Fara
Additional contact information
Laurentiu Fara: Department of Physics, Faculty of Applied Sciences, Polytechnic University of Bucharest, 060042 Bucharest, Romania
Dan Craciunescu: Department of Physics, Faculty of Applied Sciences, Polytechnic University of Bucharest, 060042 Bucharest, Romania
Silvian Fara: Department of Physics, Faculty of Applied Sciences, Polytechnic University of Bucharest, 060042 Bucharest, Romania

Energies, 2021, vol. 14, issue 10, 1-21

Abstract: The authors studied a working off-grid type photovoltaic (PV) pumping system for irrigation use. The methodology was based on digitalization analysis and numerical modeling as a preliminary stage. A mathematical model of the PV pumping installation considered the determination of the characteristic equations for all its components. These have been used together with the SISIFO simulation software to achieve the performances of the mechanical and electrical components of an advanced PV pumping system. Its global performance features, namely the monthly energy yield, monthly pumping yield, and monthly total performances (energy and flow rate) were introduced. Digital platform (DP) for PV systems characterized by three advanced technologies—machine learning (ML), digital twin (DT) and artificial intelligence (AI) was developed. The simulation results were discussed for a specific case study conducted for a location in the Southern Romania regarding the irrigation potential, taking into account the main meteorological parameters: solar irradiance and ambient temperature, related to the site. The AI approach was implemented to achieve an optimum operation of the PV pumping system by the use of the maximum power point tracking (MPPT) method and the MATLAB/Simulink software. A unified development of all the components of the PV pumping system using the SISIFO simulation software was established by the authors, with major implications in the development of solar PV installations on large-scale.

Keywords: photovoltaic pumping system; simulation tools; digital platform; performances; meteorological parameters; artificial intelligence (AI); maximum power point tracking (MPPT); control; monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/10/2778/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/10/2778/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:10:p:2778-:d:553012

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().