Systematic and critical review of optimization models for green hydrogen and ammonia supply chains

Green hydrogen and green ammonia supply chains integrate variable renewable electricity with electrolysis, nitrogen separation, ammonia synthesis, storage, transportation, reconversion, and end-use decisions. However, the optimization literature remains heterogeneous in mathematical assumptions, system boundaries, temporal representation, uncertainty treatment, adaptive decision mechanisms, and computational tractability, limiting consistent model selection and cross-study comparison. This paper presents a systematic and critical review of optimization models for integrated green hydrogen and ammonia supply chains, based on 118 studies. The review applies a controlled record-level taxonomy covering the base modeling or assessment approach, objective structure, dominant supply-chain scope, spatial scale, temporal structure, time-step resolution, uncertainty treatment, and adaptive or online mechanism. The result indicates a concentration in recent publications, regional applications, deterministic formulations, and production-oriented models. Linear and network-planning approaches, particularly mixed-integer linear programming, dominate strategic infrastructure and capacity decisions, whereas full-chain integration, dedicated storage and conversion modeling, formal stochastic and robust uncertainty treatments, and adaptive or online decision mechanisms remain underdeveloped. Building on this synthesis, the review develops a decision-oriented model-selection framework, technology-to-model matrices, uncertainty-propagation and industrial-feasibility assessments, a harmonized comparison of direct hydrogen, direct ammonia, and ammonia-to-hydrogen pathways, and a gap-to-method roadmap. Future research should prioritize hybrid multi-scale architectures integrating strategic network planning, validated nonlinear or surrogate process models, stochastic or robust optimization, decomposition, rolling-horizon control, digital twins, and lifecycle, safety, resilience, and sustainability metrics. The resulting framework supports scalable, uncertainty-aware, and industrially credible supply-chain models for integrated green hydrogen and ammonia systems.