Modeling and Optimization of Steady Flow of Natural Gas and Hydrogen Mixtures in Pipeline Networks

天然气 气体压缩机 边值问题 压气站 管道(软件) 流量(数学) 独特性 混合(物理) 数学优化 计算机科学 最优化问题 天然气 非线性系统 石油工程 工艺工程 机械 热力学 数学 工程类 机械工程 物理 废物管理 数学分析 量子力学
作者
Saif R. Kazi,Kaarthik Sundar,Shriram Srinivasan,Anatoly Zlotnik
出处
期刊:Cornell University - arXiv 被引量:2
标识
DOI:10.48550/arxiv.2212.00961
摘要

We extend the canonical problems of simulation and optimization of steady-state gas flows in pipeline networks with compressors to the transport of mixtures of highly heterogeneous gases injected throughout a network. Our study is motivated by proposed projects to blend hydrogen generated using clean energy into existing natural gas pipeline systems as part of efforts to reduce the reliance of energy systems on fossil fuels. Flow in a pipe is related to endpoint pressures by a basic Weymouth equation model, with an ideal gas equation of state, where the wave speed depends on the hydrogen concentration. At vertices, in addition to mass balance, we also consider mixing of incoming flows of varying hydrogen concentrations. The problems of interest are the heterogeneous gas flow simulation (HGFS), which determines system pressures and flows given fixed boundary conditions and compressor settings, as well as the heterogeneous gas flow optimization (HGFO), which extremizes an objective by determining optimal boundary conditions and compressor settings. We examine conditions for uniqueness of solutions to the HGFS, as well as compare and contrast mixed-integer and continuous nonlinear programming formulations for the HGFO. We develop computational methods to solve both problems, and examine their performance using four test networks of increasing complexity.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
Stitch完成签到 ,获得积分10
刚刚
刚刚
眯眯眼的冷珍完成签到,获得积分10
刚刚
bjyx完成签到,获得积分10
刚刚
reck完成签到,获得积分10
1秒前
pharmstudent发布了新的文献求助30
1秒前
小田完成签到,获得积分10
1秒前
小喵发布了新的文献求助10
2秒前
FashionBoy应助毛毛哦啊采纳,获得10
2秒前
Lucas应助Chen采纳,获得10
3秒前
强健的蚂蚁完成签到,获得积分20
3秒前
小宇发布了新的文献求助10
3秒前
斜杠武完成签到,获得积分20
3秒前
4秒前
伞兵龙发布了新的文献求助10
4秒前
RC_Wang应助科研小民工采纳,获得10
4秒前
sanben完成签到,获得积分10
4秒前
4秒前
_蝴蝶小姐完成签到,获得积分10
5秒前
诗轩发布了新的文献求助10
6秒前
6秒前
6秒前
6秒前
6秒前
6秒前
迟大猫应助乐乱采纳,获得10
7秒前
万能图书馆应助派大星采纳,获得10
8秒前
FashionBoy应助娜行采纳,获得10
9秒前
9秒前
传奇3应助后知后觉采纳,获得10
10秒前
10秒前
10秒前
科研通AI2S应助Chem is try采纳,获得10
10秒前
11秒前
a方舟发布了新的文献求助10
11秒前
寒冷书竹发布了新的文献求助10
11秒前
11秒前
hhh发布了新的文献求助10
11秒前
顾矜应助富婆嘉嘉子采纳,获得10
11秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527304
求助须知:如何正确求助?哪些是违规求助? 3107454
关于积分的说明 9285518
捐赠科研通 2805269
什么是DOI,文献DOI怎么找? 1539827
邀请新用户注册赠送积分活动 716708
科研通“疑难数据库(出版商)”最低求助积分说明 709672