← 論文一覧に戻る

Techno-Economic Assessment of a Hybrid Offshore Wind–Tidal System for Green Hydrogen Production and Maritime Export in Morocco

モロッコにおける洋上風力・潮力ハイブリッドシステムによるグリーン水素生産と海上輸出の技術経済評価 (AI 翻訳)

Farnini OE, Trihi M

Research Squareプレプリント2026-07-14#水素Origin: Global経営インパクト: コスト削減対象セクター: energy
DOI: 10.20944/preprints202607.0950.v1
原典: https://doi.org/10.20944/preprints202607.0950.v1

🤖 gxceed AI 要約

日本語

モロッコの大西洋サハラ沖の洋上風力と潮力を組み合わせた560MWハイブリッド発電で水素を製造し、液化水素として輸送する技術経済モデルを構築。2025年ベースで生産LCOHは7.53 USD/kg、2030年には4.45 USD/kgと試算され、ロードマップ目標に接近。ハイブリッド化により出力変動が低減し、電解槽の稼働率向上に寄与する。

English

This study presents a techno-economic model of a 560 MW hybrid offshore wind-tidal hub in Morocco producing green hydrogen via PEM electrolysis and exporting it as liquid hydrogen. The 2025 levelised cost is 7.53 USD/kg (delivered 10.04 USD/kg), dropping to 4.45 USD/kg by 2030 under learning assumptions. Hybridisation reduces output variance and electrolyser cycling, approaching national roadmap targets.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本は水素基本戦略で大量の海外水素輸入を計画しており、本論文のモロッコ事例はアフリカからの水素サプライチェーン構想の参照点となる。また、洋上風力と潮力のハイブリッドによる安定供給モデルは、日本の離島や海洋資源活用にも示唆を与える。

In the global GX context

This paper provides a transparent, reproducible model for green hydrogen production from hybrid offshore renewables, relevant to global hydrogen trade discussions under the Hydrogen Breakthrough Agenda. The cost trajectory (4.45 USD/kg by 2030) aligns with competitiveness benchmarks for maritime export, informing ISSB/TCFD-aligned disclosure on hydrogen project economics.

👥 読者別の含意

🔬研究者:Offers a validated open-source framework for wind–tidal hydrogen modelling, suitable for multi-objective optimisation and replication in other coastal contexts.

🏢実務担当者:Provides cost benchmarks and sensitivity drivers for project developers evaluating hybrid offshore hydrogen production and liquefaction value chains.

🏛政策担当者:Demonstrates that hybrid offshore renewables can reduce hydrogen production cost volatility, supporting national hydrogen roadmap targets and export strategies.

📄 Abstract(原文)

Morocco’s National Green Hydrogen Roadmap targets large-scale hydrogen exports, yet the offshore wind and tidal resources of the Atlantic Sahara coast remain underexplored, and single-resource electrolysis plants suffer from low, variable electrolyser utilisation. This study presents a reproducible techno-economic model of a 560 MW hybrid offshore wind–tidal hub at Dakhla producing hydrogen via proton-exchange-membrane (PEM) electrolysis and exporting it as liquid hydrogen (LH₂) to Jorf Lasfar (1,241 km). The regional wind, current and sea-surface-temperature resource is characterised from Copernicus Marine Service (CMEMS) reanalysis and satellite products (2002–2016), complemented by ERA5 hourly wind for the Weibull fit; the framework then integrates harmonic (M₂+S₂) tidal modelling, Jensen wake losses, hourly dispatch, liquefaction, shipping, and discounted levelised-cost-of-hydrogen (LCOH) analysis. For a 510/50 MW wind/tidal configuration feeding a 350 MW electrolyser, capacity factors reach 49.1 % (wind), 8.8 % (tidal) and 45.5 % (hybrid), yielding ≈36,800 t H₂/yr at 60 % utilisation with 15.1 % curtailment. The 2025 base-case production LCOH is 7.53 USD/kg (10.04 USD/kg delivered); a 2030 learning scenario reduces this to 4.45 USD/kg, approaching the 2–4 USD/kg roadmap band. Hybridisation provides firming value through near-zero wind–tidal correlation, reducing output variance and electrolyser cycling rather than adding energy. Sensitivity analysis identifies capacity factor and electrolyser specific energy consumption as the dominant cost drivers, ahead of wind capital cost and the cost of capital. This work offers the first integrated wind–tidal hydrogen assessment for the Moroccan Atlantic coast and a transparent modelling platform for future multi-objective optimisation.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。