Optimal scheduling of a zero-carbon integrated energy system based on electrical substitution
電気代替に基づくゼロカーボン統合エネルギーシステムの最適スケジューリング (AI 翻訳)
Xin Zhang, H. Mu
🤖 gxceed AI 要約
日本語
産業団地向けに風力・太陽光・水素を統合したゼロカーボンエネルギーシステムを提案。NSGA-IIとCPLEXを組み合わせた多目的最適化により、年間エネルギーコスト91%削減、エネルギー自給率89%、炭素排出量86%削減を実証した。本システムは低炭素化改修と容量計画の実践的ガイドラインを提供する。
English
This paper proposes a wind-solar-hydrogen integrated energy system for near-zero carbon industrial parks. Using a multi-objective scheduling model solved by NSGA-II and CPLEX, it achieves 91% annual cost reduction, 89% energy self-sufficiency, and 86% carbon emission reduction. The study provides practical guidelines for low-carbon retrofitting and capacity planning.
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
日本の産業団地における脱炭素化とSSBJへの対応に直接貢献する。本システムはエネルギーコスト削減と排出削減を両立し、有報や統合報告書での開示強化にも役立つ実証データを提供する。
In the global GX context
This paper aligns with global trends like ISSB and CSRD by offering a replicable model for industrial decarbonization. The quantitative results support transition finance and policy making for net-zero industrial parks.
👥 読者別の含意
🔬研究者:Provides a validated multi-objective scheduling framework combining NSGA-II and CPLEX for integrated energy systems, useful for further optimization studies.
🏢実務担当者:Can directly apply the proposed architecture and operational strategy for low-carbon retrofitting of industrial parks, achieving significant cost and emission reductions.
🏛政策担当者:Offers quantitative evidence supporting policy incentives for electrical substitution and green hydrogen in industrial decarbonization.
📄 Abstract（原文）
To address the pressing decarbonization demands of industrial parks, this paper proposes a novel wind-solar-hydrogen integrated energy system (IES) architecture tailored for near-zero carbon operations. Phasing out conventional fossil-fuel reliance, the proposed framework leverages electrical substitution and green hydrogen production to construct a deeply coupled multi-energy network encompassing electricity, heat, cooling, and hydrogen. To simultaneously maximize economic viability, environmental sustainability, and energy independence, we establish a multi-objective synergistic scheduling model, which is efficiently solved using a hybrid approach combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the CPLEX solver. Extensive simulations of a real-world case study demonstrate that the optimized operational strategy slashes the annual net energy cost by 91%, boosts the comprehensive energy self-sufficiency rate to 89%, and reduces carbon emission intensity by 86%. This study rigorously validates the techno-economic feasibility of the proposed near-zero carbon architecture, providing robust quantitative theoretical support and practical engineering guidelines for the low-carbon retrofitting and capacity planning of emerging industrial parks.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1088/1742-6596/3269/1/012046first seen 2026-07-06 05:18:08
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