Day-Ahead Scheduling Optimization Model of a Natural Gas Pipeline Network Considering User’s Hourly Consumption Characteristics

In the scheduling of natural gas for hourly distribution, the network features a variety of control modes and diverse consumer types. Currently, there is a deficiency in the precise management of hourly distribution tailored to specific consumers. This study developed an optimization model for the hourly distribution in natural gas networks, grounded in control mode theory. The model’s objective function is designed to minimize the energy consumption of network compressors, subject to constraints imposed by four control modes: quota completion cutoff, equal distribution over remaining hours, improved equal distribution over remaining hours, and the weighted coefficient. Utilizing an independent time layer approach, the hourly distribution optimization model (HDO model) identifies the optimal control mode for various consumer types. Validation through a case study and comparative analysis with the daily operation optimization model (DOO model) in natural gas networks illustrated the beneficial impact of incorporating control modes on operational efficiency. The results show that by implementing this distribution scheme in a multiuser natural gas network, the HDO model reduces compressor energy consumption by 8.11% compared with the DOO model. This underscores the critical role of integrating control modes into the optimization process, laying the foundation for the stable and efficient operation of the natural gas network.

Authors

Institutions

Publication Details

Journal
Journal of Pipeline Systems Engineering and Practice
Published
2025-02-06
DOI
https://doi.org/10.1061/jpsea2.pseng-1734
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Day-Ahead Scheduling Optimization Model of a Natural Gas Pipeline Network Considering User’s Hourly Consumption Characteristics

Shitao Liu, Jun Zhou, Zihao Xiong, Qifeng Shen et al.
1 citations
Journal of Pipeline Systems Engineering and Practice
Integrated Energy Systems Optimization
0.73
article

Day-Ahead Scheduling Optimization Model of a Natural Gas Pipeline Network Considering User’s Hourly Consumption Characteristics

Shitao Liu, Jun Zhou, Zihao Xiong, Qifeng Shen, Guangchuan Liang
article en
1 citations

Abstract

In the scheduling of natural gas for hourly distribution, the network features a variety of control modes and diverse consumer types. Currently, there is a deficiency in the precise management of hourly distribution tailored to specific consumers. This study developed an optimization model for the hourly distribution in natural gas networks, grounded in control mode theory. The model’s objective function is designed to minimize the energy consumption of network compressors, subject to constraints imposed by four control modes: quota completion cutoff, equal distribution over remaining hours, improved equal distribution over remaining hours, and the weighted coefficient. Utilizing an independent time layer approach, the hourly distribution optimization model (HDO model) identifies the optimal control mode for various consumer types. Validation through a case study and comparative analysis with the daily operation optimization model (DOO model) in natural gas networks illustrated the beneficial impact of incorporating control modes on operational efficiency. The results show that by implementing this distribution scheme in a multiuser natural gas network, the HDO model reduces compressor energy consumption by 8.11% compared with the DOO model. This underscores the critical role of integrating control modes into the optimization process, laying the foundation for the stable and efficient operation of the natural gas network.

Journal of Pipeline Systems Engineering and PracticeVol. 16(2)
Sinopec (China) (CN), Southwest Petroleum University (CN)
Affordable and clean energy
Openalex Percentile: Top 32%
Integrated Energy Systems Optimization
0.73
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.