Probabilistic Assessment of Solar-Based Hydrogen Production Using PVGIS, Metalog Distributions, and LCOH Modeling

Jacek Caban (), Arkadiusz Małek () and Zbigniew Siemiątkowski
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Jacek Caban: Department of Automation, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
Arkadiusz Małek: Department of Transportation and Informatics, WSEI University, Projektowa 4, 20-209 Lublin, Poland
Zbigniew Siemiątkowski: Faculty of Mechanical Engineering, Casimir Pulaski Radom University, ul. Stasieckiego 54, 26-600 Radom, Poland

Energies, 2025, vol. 18, issue 18, 1-28

Abstract: The transition toward low-carbon energy systems requires reliable tools for assessing renewable-based hydrogen production under real-world climatic and economic conditions. This study presents a novel probabilistic framework integrating the following three complementary elements: (1) a Photovoltaic Geographical Information System (PVGIS) for high-resolution, location-specific solar energy data; (2) Metalog probability distributions for advanced modeling of variability and uncertainty in photovoltaic (PV) energy generation; and (3) Levelized Cost of Hydrogen (LCOH) calculations to evaluate the economic viability of hydrogen production systems. The methodology is applied to three diverse European locations—Lublin (Poland), Budapest (Hungary), and Malaga (Spain)—to demonstrate regional differences in hydrogen production potential. The results indicate annual PV energy yields of 108.3 MWh, 124.6 MWh, and 170.95 MWh, respectively, which translate into LCOH values of EUR 9.67/kg (Poland), EUR 8.40/kg (Hungary), and EUR 6.13/kg (Spain). The probabilistic analysis reveals seasonal production risks and quantifies the probability of achieving specific monthly energy thresholds, providing critical insights for designing systems with continuous hydrogen output. This combined use of a PVGIS, Metalog, and LCOH calculations offers a unique decision-support tool for investors, policymakers, and SMEs planning green hydrogen projects. The proposed methodology is scalable and adaptable to other renewable energy systems, enabling informed investment decisions and improved regional energy transition strategies.

Keywords: renewable energy sources; renewable energy developers; hydrogen electrolyzer; low-emission hydrogen; Metalog; artificial intelligence; LCOH (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
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