Process-Integrated Hydrogen Energy Storage, Carbon Capture, and PEV Coordination in Renewable-Assisted Power Systems: A Chemical Engineering Optimization Perspective
プロセス統合型水素エネルギー貯蔵、炭素回収、および再生可能エネルギー支援電力系統におけるPEV連携：化学工学最適化の観点から (AI 翻訳)
Abhilasha Pawar, Y V Krishna Reddy, Víctor Daniel Jiménez Macedo, Lizina Khatua, Feroz Shaik, Subhasis Datta, Kamalika Tiwari, C. KARNAN
🤖 gxceed AI 要約
日本語
本論文は、水素エネルギー貯蔵と燃焼後炭素回収を統合した再生可能エネルギー支援電力システムの最適化フレームワークを提案。電気自動車（PEV）のV2G機能も考慮し、多目的最適化問題として定式化。標準テストシステムでの評価により、再生可能エネルギーとPEVの統合で排出量19％、運転コスト10％削減。水素貯蔵と90％効率の炭素回収により約80％の排出削減を達成。化学工学的アプローチの有効性を示す。
English
This study presents a process-integrated optimization framework for hydrogen energy storage and post-combustion carbon capture in renewable-assisted power systems, incorporating plug-in electric vehicles (PEVs) with V2G capability. Multi-objective optimization using Zebra Optimization Algorithm achieves 19% emission reduction and 10% cost reduction with renewables and PEVs, and up to 80% emission reduction with hydrogen storage and 90% efficient carbon capture.
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
日本では、水素基本戦略やCCS長期ロードマップが進む中、水素貯蔵とCCSを電力系統最適化に組み込む本手法は、再生可能エネルギー大量導入時の系統安定化と脱炭素化に示唆を与える。PEVとの連携も、日本自動車産業の電動化戦略と親和性が高い。
In the global GX context
This framework aligns with global efforts to integrate hydrogen and carbon capture into power system decarbonization. The process-oriented modeling approach offers a template for system operators and utilities planning to incorporate hydrogen storage and CCS while optimizing costs and emissions. The inclusion of V2G capability reflects trends in smart grid and transport electrification.
👥 読者別の含意
🔬研究者:Provides a detailed chemical engineering optimization model for integrating hydrogen and carbon capture with PEVs, offering a benchmark for multi-objective energy system studies.
🏢実務担当者:Utility planners and grid operators can use the framework to evaluate cost-emission trade-offs when deploying hydrogen storage and CCS in renewable-rich grids.
🏛政策担当者:Demonstrates that coordinated hydrogen and CCS can achieve deep decarbonization (80% reduction) at moderate cost, informing national energy and climate strategies.
📄 Abstract（原文）
This study presents a process-integrated framework for hydrogen energy storage and post-combustion carbon capture within renewable-assisted power systems, explicitly incorporating plug-in electric vehicle (PEV) interactions. In contrast to conventional economic load dispatch (ELD) formulations that treat hydrogen and carbon capture as simplified energy components, the proposed approach adopts a process-oriented representation of electrolyzer-based hydrogen production, fuel cell energy conversion, and amine-based CO₂ absorption. The framework captures the coupling between electrical energy flows and chemical processes through energy–mass balance relationships and efficiency constraints. PEVs are modelled as flexible electrochemical storage systems with bidirectional vehicle-to-grid (V2G) capability, enabling dynamic interaction with system demand. The integrated model is formulated as a multi-objective optimization problem, considering operating cost and emission reduction, and is solved using the Zebra Optimization Algorithm (ZOA). The framework is evaluated on a standard ten-unit test system under multiple operational scenarios. Results indicate that renewable and PEV integration reduces emissions by 19% and operating cost by 10%. The inclusion of hydrogen energy storage and 90% efficient carbon capture achieves approximately 80% emission reduction with a moderate increase in cost. These findings highlight the significance of incorporating process-level chemical engineering principles into power system optimization, demonstrating that coordinated hydrogen production, utilization, and carbon capture can substantially enhance decarbonization performance while maintaining system feasibility.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.59429/ace.v9i2.5970first seen 2026-06-14 04:53:24 · last seen 2026-06-14 04:53:30
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