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Analyzing solar location for green hydrogen using multi-criteria decision analysis

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  • Janmontree, Jettarat
  • Zadek, Hartmut
  • Ransikarbum, Kasin

Abstract

Hydrogen energy demand has grown remarkably to support applications around the globe. This study evaluates the green hydrogen supply chain's upstream process, specifically using electricity from solar energy in electrolysis. The focus is on identifying potential locations for solar photovoltaics based on geographic, climate, and solar criteria. The study uses Saxony-Anhalt in Germany as a case study, evaluating eleven districts and three independent cities as decision-making units to determine their efficiency in hydrogen production. The methodology employed is an integrated multi-criteria decision analysis framework to evaluate these alternatives under competing criteria. Initially, the data envelopment analysis method assesses each alternative's efficiency. Following this, the super-efficiency data envelopment analysis technique is applied to rank the efficient decision-making units. To validate the results, they are compared using the entropy weight method and the technique for order of preference by similarity to ideal solution. A techno-economic analysis is then conducted to simulate hydrogen production volume and cost, considering the efficiency of the installed solar photovoltaic plant and electrolyzer. The analysis shows that 57 % of all the evaluated alternatives are relatively efficient. Moreover, the Halle (Saale) district is identified as the most suitable location for hydrogen production based on efficiency and cost criteria. The findings provide a strategic policy model for further hydrogen supply chain development across upstream, midstream, and downstream operations.

Suggested Citation

  • Janmontree, Jettarat & Zadek, Hartmut & Ransikarbum, Kasin, 2025. "Analyzing solar location for green hydrogen using multi-criteria decision analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:rensus:v:209:y:2025:i:c:s1364032124008281
    DOI: 10.1016/j.rser.2024.115102
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