Comprehensive Energy and Economic Analysis of Selected Variants of a Large-Scale Photovoltaic Power Plant in a Temperate Climate
Dennis Thom,
Artur Bugała (),
Dorota Bugała and
Wojciech Czekała ()
Additional contact information
Dennis Thom: Faculty of Automatic, Robotics and Electrical Engineering, Institute of Electrical Engineering and Electronics, Poznań University of Technology, St. Piotrowo 3a, 60-965 Poznań, Poland
Artur Bugała: Faculty of Automatic, Robotics and Electrical Engineering, Institute of Electrical Engineering and Electronics, Poznań University of Technology, St. Piotrowo 3a, 60-965 Poznań, Poland
Dorota Bugała: Faculty of Automatic, Robotics and Electrical Engineering, Institute of Electrical Engineering and Electronics, Poznań University of Technology, St. Piotrowo 3a, 60-965 Poznań, Poland
Wojciech Czekała: Department of Biosystems Engineering, Poznań University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland
Energies, 2025, vol. 18, issue 15, 1-32
Abstract:
In recent years, solar energy has emerged as one of the most advanced renewable energy sources, with its production capacity steadily growing. To maximize output and efficiency, choosing the right configuration for a specific location for these installations is crucial. This study uniquely integrates detailed multi-variant fixed-tilt PV system simulations with comprehensive economic evaluation under temperate climate conditions, addressing site-specific spatial constraints and grid integration considerations that have rarely been combined in previous works. In this paper, an energy and economic efficiency analysis for a photovoltaic power plant, located in central Poland, designed in eight variants (10°, 15°, 20°, 25°, 30° PV module inclination angle for a south orientation and 10°, 20°, 30° for an east–west orientation) for a limited building area of approximately 300,000 m 2 was conducted. In PVSyst computer simulations, PVGIS-SARAH2 solar radiation data were used together with the most common data for describing the Polish local solar climate, called Typical Meteorological Year data (TMY). The most energy-efficient variants were found to be 20° S and 30° S, configurations with the highest surface production coefficient (249.49 and 272.68 kWh/m 2 ) and unit production efficiency values (1123 and 1132 kWh/kW, respectively). These findings highlight potential efficiency gains of up to approximately 9% in surface production coefficient and financial returns exceeding 450% ROI, demonstrating significant economic benefits. In economic terms, the 15° S variant achieved the highest values of financial parameters, such as the return on investment (ROI) (453.2%), the value of the average annual share of profits in total revenues (56.93%), the shortest expected payback period (8.7 years), the value of the levelized cost of energy production (LCOE) (0.1 EUR/kWh), and one of the lowest costs of building 1 MWp of a photovoltaic farm (664,272.7 EUR/MWp). Among the tested variants of photovoltaic farms with an east–west geographical orientation, the most advantageous choice is the 10° EW arrangement. The results provide valuable insights for policymakers and investors aiming to optimize photovoltaic deployment in temperate climates, supporting the broader transition to renewable energy and alignment with national energy policy goals.
Keywords: photovoltaic power plant; multi-criteria evaluation; photovoltaic potential; economic analysis of RES investments (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: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/18/15/4198/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/15/4198/ (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:18:y:2025:i:15:p:4198-:d:1719641
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 ().