Optimized Operation of Hydrogen Pipeline Networks Considering Thermal Safety of Hydrogen Storage Tanks

With the growing demand for clean energy, hydrogen has emerged as a key zero-carbon energy carrier, particularly in power-to-hydrogen (P2H) systems. However, the safe operation of hydrogen storage tanks-especially during rapid charging/discharging-remains a critical yet understudied challenge. This paper proposes an optimized electricity-hydrogen network model that ensures thermal safety in hydrogen storage tanks during rapid charging/discharging. The framework integrates power grid and pipeline network optimization with a neural network-based thermal surrogate model. Case studies show the model prevents hazardous temperature fluctuations with only a 2.4% cost increase, demonstrating its effectiveness for safe hydrogen system operation.

Authors

Institutions

Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1109/nesp65198.2025.11041005
Primary Topic
Hybrid Renewable Energy Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimized Operation of Hydrogen Pipeline Networks Considering Thermal Safety of Hydrogen Storage Tanks

Yidong Wu, Yuntian Zhu, Wendi Zheng, Jianing Pan et al.
Hybrid Renewable Energy Systems
article

Optimized Operation of Hydrogen Pipeline Networks Considering Thermal Safety of Hydrogen Storage Tanks

Yidong Wu, Yuntian Zhu, Wendi Zheng, Jianing Pan, Rui Chen
article en

Abstract

With the growing demand for clean energy, hydrogen has emerged as a key zero-carbon energy carrier, particularly in power-to-hydrogen (P2H) systems. However, the safe operation of hydrogen storage tanks-especially during rapid charging/discharging-remains a critical yet understudied challenge. This paper proposes an optimized electricity-hydrogen network model that ensures thermal safety in hydrogen storage tanks during rapid charging/discharging. The framework integrates power grid and pipeline network optimization with a neural network-based thermal surrogate model. Case studies show the model prevents hazardous temperature fluctuations with only a 2.4% cost increase, demonstrating its effectiveness for safe hydrogen system operation.

Fujian Electric Power Survey & Design Institute (CN), Fuzhou University (CN)
Affordable and clean energy
Openalex Percentile: Top 86%
Hybrid Renewable Energy Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.