Study Generates Diverse Near-Optimal Paths for European Green E‑Molecule Imports

Global: Study Generates Diverse Near-Optimal Paths for European Green E‑Molecule Imports

Researchers Mahdi Kchaou, Francesco Contino, and Diederik Coppitters posted a new preprint on arXiv on 29 December 2025 that explores alternative designs for importing green e‑molecules such as hydrogen, ammonia, methane, and methanol. The work addresses the fragility of single cost‑optimal solutions by producing a suite of near‑cost‑optimal pathways that remain within a 10 % cost margin of the best‑case scenario. The study is framed within the broader European energy transition, where regulatory, spatial, and stakeholder constraints can render theoretically optimal designs impractical.

Modeling to Generate Alternatives Approach

The authors employ a technique called Modeling to Generate Alternatives (MGA), which systematically explores the solution space around the cost optimum while accounting for uncertainties that are difficult to encode in traditional optimization models. MGA creates a diverse portfolio of feasible designs, allowing decision‑makers to evaluate trade‑offs without committing to a single, potentially brittle solution.

Interpretable Machine Learning Analysis

To extract actionable insights from the large set of generated alternatives, the team applies interpretable machine learning methods. These algorithms identify which input variables most strongly influence cost and feasibility, providing a transparent view of the factors that drive flexibility in import pathway design.

Application to Hydrogen, Ammonia, Methane, and Methanol Carriers

The methodology is tested on four primary carriers of green e‑molecules: hydrogen, ammonia, methane, and methanol. By modeling each carrier’s supply chain—including production, conversion, transport, and storage—the researchers assess how variations in renewable generation (solar and wind) and storage capacity affect overall costs.

Flexibility Findings Within 10% Cost Margin

Results reveal a broad near‑optimal space, indicating that strict reliance on any single renewable source or storage technology is unnecessary to stay within 10 % of the cost optimum. Specifically, wind‑constrained scenarios tend to favor solar‑storage methanol pathways, whereas limited storage capacity shifts the preference toward wind‑driven ammonia or methane routes. This flexibility suggests that policymakers can accommodate regional resource availability without sacrificing economic competitiveness.

Policy and Planning Implications

The study’s findings support more resilient infrastructure planning by highlighting multiple viable configurations rather than a single “best” design. Regulators and industry stakeholders can use the identified alternatives to negotiate permits, align with local renewable potential, and mitigate risks associated with future regulatory changes.

Limitations and Future Work

While the preprint provides a comprehensive proof‑of‑concept, it relies on abstract‑level data and does not incorporate detailed site‑specific constraints or dynamic market conditions. The authors recommend extending the analysis with real‑world case studies and integrating temporal price fluctuations to further refine pathway selection.

This report is based on information from arXiv, licensed under Academic Preprint / Open Access. Based on the abstract of the research paper. Full text available via ArXiv.