طراحی شبکه زنجیره تامین هیدروژن و برنامه ریزی ایستگاه سوخت
ترجمه نشده

طراحی شبکه زنجیره تامین هیدروژن و برنامه ریزی ایستگاه سوخت

عنوان فارسی مقاله: مدل بهینه سازی یکپارچه برای طراحی شبکه زنجیره تامین هیدروژن و برنامه ریزی ایستگاه سوخت رسانی هیدروژن
عنوان انگلیسی مقاله: Integrated optimization model for hydrogen supply chain network design and hydrogen fueling station planning
مجله/کنفرانس: کامپیوترها و مهندسی شیمی - Computers & Chemical Engineering
رشته های تحصیلی مرتبط: مهندسی شیمی
کلمات کلیدی فارسی: یکپارچگی، مدل بهینه سازی، شبکه زنجیره تامین هیدروژن، ایستگاه سوخت رسانی هیدروژن، MILP
کلمات کلیدی انگلیسی: Integration، Optimization model، Hydrogen supply chain network، Hydrogen fueling station، MILP
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus - Master Journals List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.compchemeng.2019.106683
دانشگاه: Univ. Bourgogne Franche-Comté FEMTO-ST Institute/CN RS, UTBM, rue Thierry-Mieg, Belfort Cedex 90 010, France
صفحات مقاله انگلیسی: 65
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 3/800 در سال 2019
شاخص H_index: 124 در سال 2020
شاخص SJR: 0/932 در سال 2019
شناسه ISSN: 0098-1354
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
آیا این مقاله مدل مفهومی دارد: دارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: دارد
کد محصول: E14746
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1- Introduction

2- Literature review

3- Problem description

4- Mathematical model

5- Case study: Franche-Comté, France

6- Results and discussion

7- Conclusion

References

بخشی از مقاله (انگلیسی)

Abstract

This paper focuses on developing a mathematical model that covers the entire hydrogen supply network. The classical hydrogen supply chain network design (HSCND) model is integrated with the hydrogen fueling station planning (HFSP) model to generate a new formulation. The proposed model considers the feedstock supply, the installation and operation of hydrogen facilities, the operation of transportation technologies, and the carbon capture and storage (CCS) system. Two primary hydrogen fueling technologies, namely on-site fueling (hydrogen is produced on-site) and standard fueling (hydrogen is delivered by road), are considered. The problem is formulated as a mixed-integer linear programming (MILP) model that minimizes the least cost of hydrogen (LCOH). The necessity of considering various components within a single framework is demonstrated through a case study in Franche-Comté, France. The role of each key model component (such as the fueling technology, feedstock transportation, and CCS system) is analyzed. The proposed model is capable of studying the interactions that exist between different parts of a hydrogen supply network. Consequently, more comprehensive construction plans for the HSCN are guaranteed.

Introduction

The transportation sector is one of the most significant contributors to greenhouse gas (GHG) emissions. It accounted for 26% of EU, 28% of U.S., and 23% worldwide of total GHG emissions in recent years (Environmental Protection Agency, 2018; European Environment Agency, 2017; Sims et al., 2014). Within the sector, road transportation is by far the largest category, contributing approximately three-quarters of all emissions (International Energy Agency, 2015). Aggressive and sustained mitigation strategies are essential if deep GHG reduction ambitions, such as the two-degree scenario, are to be achieved. To this end, the equivalent of 160 million low-emission vehicles will need to be on the roads by 2030, according to International Energy Agency (2017). It is widely accepted that hydrogen is a critical element in the decarbonization of the transporta tion sector, which still relies almost exclusively on oil (McKinsey & Company, 2017). Hydrogen can be used in electric vehicles (EVs) equipped with hydrogen fuel cells (FCEV). FCEVs are a nec essary complement to battery electric vehicles (BEVs) as FCEVs add convenience for consumers with long ranges and fast fueling times. FCEVs can also provide potentially very low carbon emissions (International Energy Agency, 2015). In terms of cost per mile, FCEVs will need tax credits or other subsidies to be competitive with conventional cars and other types of alternative fuel vehicles during the early stages of commercial implementation (M. Ruth, T.A. Timbario & Laffen, 2011). However, significant cost reduction can be realized by scaling up manufacturing of FCEVs and hydrogen fueling infrastructures (McKinsey & Company, 2017).