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風力・太陽光・蓄電統合によるコークス副生ガスからのメタノール生産における容量配分と運用スケジューリングの協調最適化

Coordinated Optimization of Capacity Allocation and Operational Scheduling for Methanol Production from Coking By-Products with Wind-Solar-Storage Integration (原題)

Xiaoming Zhang, Baozhou Ding, Haojie Cheng, Zhangzhuo Sun, Qiang Wang

Energy Engineering📚 査読済 / ジャーナル2026-01-01#エネルギー転換Origin: CN経営インパクト: コスト削減対象セクター: manufacturing
DOI: 10.32604/ee.2026.089458
原典: https://doi.org/10.32604/ee.2026.089458
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🤖 gxceed AI 要約

日本語

中国のコークス工場を対象に、風力・太陽光・蓄電池とCOG-to-メタノール生産を統合したマルチエネルギーシステムを提案。K-meansクラスタリングで季節代表日を構築し、上層でPSOによる容量設計、下層でMILPによる運用最適化を行う。ケーススタディでは年間純収益3378万元、再生可能エネルギー出力抑制ゼロ、COG放出ゼロを達成し、提案手法の有効性を示した。

English

This study proposes a multi-energy system integrating wind, solar, battery storage, and COG-to-methanol production for coking plants. Using K-means clustering for seasonal representative days, a bi-level optimization (PSO for capacity, MILP for scheduling) achieves annual net revenue of CNY 33.78 million with zero renewable curtailment and zero COG venting, demonstrating effectiveness and adaptability.

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

日本の鉄鋼・コークス産業はCO2排出削減が急務であり、副生ガスの有効活用と再エネ統合はSSBJ開示や移行戦略に資する。本手法は工場内のエネルギー最適化の具体例として、日本の製造業の脱炭素計画に示唆を与える。

In the global GX context

This work contributes to global decarbonization of hard-to-abate industrial sectors by integrating renewable energy with CCU in coking. It offers a replicable optimization framework for industrial symbiosis, relevant to ISSB-aligned transition planning and low-carbon investment decisions.

👥 読者別の含意

🔬研究者:Provides a bi-level optimization framework for multi-energy systems integrating renewables and CCU, with seasonal clustering and algorithm comparison.

🏢実務担当者:Offers a model for coking plants to reduce emissions and generate revenue through methanol production, aiding transition strategy and disclosure.

🏛政策担当者:Demonstrates a pathway for industrial decarbonization that aligns with dual-carbon goals, informing policy support for CCU and renewable integration.

📄 Abstract（原文）

: Under China’s dual-carbon goals, integrating renewable energy sources such as wind and solar power provides an effective pathway for the low-carbon transition of coking plants. However, renewable-generation variability may cause energy supply–demand imbalances. Meanwhile, coke oven gas (COG) and associated industrial CO 2 from coking retain considerable potential for value-added utilization. Existing studies rarely integrate renewable-energy utilization, COG storage and regulation, CO 2 utilization, methanol synthesis, and methanol storage and sales in a unified framework. Therefore, this study develops a multi-energy system coupling wind power, photovoltaics, battery storage, and COG-to-methanol production, and establishes a coordinated optimization model for capacity configuration and operational scheduling. K-means clustering constructs representative days for spring, summer, autumn, and winter. The upper-level model uses particle swarm optimization to determine the capacities of wind power, photovoltaics, battery energy storage, the COG holder, the methanol synthesis unit, and the methanol storage tank, while the lower-level model uses mixed-integer linear programming to coordinate electricity, gas, and methanol flows. Assuming a fixed capacity for the existing gas turbine and constant material and energy conversion coefficients for methanol production, the case-study results show a projected annual net revenue of CNY 33.78 million, with zero annual renewable-energy curtailment and zero COG venting. Algorithm comparisons and scenario analyses involving renewable-energy output variations, economic parameters, and equipment failures further demonstrate the solution framework’s effectiveness and the proposed system’s operational adaptability. Because four seasonal representative days are used, the model does not fully capture the entire year’s continuous 8760-h chronology.

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