Energy Consumption Optimization Model of Large Parallel Natural Gas Pipeline Network: Using Compressors with Multiple Operating Modes-Reference-Cited by-同舟云学术

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Energy Consumption Optimization Model of Large Parallel Natural Gas Pipeline Network: Using Compressors with Multiple Operating Modes

Published:2022-12-07 Issue:1 Volume:37 Page:774-784
ISSN:0887-0624
Container-title:Energy & Fuels
language:en
Short-container-title:Energy Fuels

Author:

Liu Enbin¹^ORCID,Peng Yong¹,Ji Yongqiang²,Azimi Mohammadamin³,Shi Laimin⁴

Affiliation:

1. Petroleum Engineering School, Southwest Petroleum University, Chengdu610500, China

2. China Petroleum & Chemical Co., Ltd. of North Branch, Zhengzhou450006, China

3. Trenchless Technology Center, Louisiana Tech University, Ruston, Louisiana71270, United States

4. Zhejiang Zheneng Natural Gas Operation Co., Ltd., Hangzhou, 310051, China

Funder

Southwest Petroleum University

the Natural Science Foundation of Sichuan Province

Publisher

American Chemical Society (ACS)

Subject

Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.energyfuels.2c02929

Reference41 articles.

1. A review on the natural gas potential of Pakistan for the transition to a low-carbon future

2. Sino-Russian natural gas cooperation: structure and situation

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1. Optimization research on energy consumption and carbon emissions in hydrogen-blended natural gas pipeline networks considering compressor performance - A case study of the west-east gas pipeline (line 1);International Journal of Hydrogen Energy;2024-08

2. Operation Optimization of Natural Gas Pipe Network Considering Energy Metering;Journal of Pipeline Systems Engineering and Practice;2024-08

3. Enhanced short-term load forecasting with hybrid machine learning models: CatBoost and XGBoost approaches;Expert Systems with Applications;2024-05

4. Pipe sharing: A bilevel optimization model for the optimal capacity allocation of natural gas network;Applied Energy;2024-04

5. Research on Intelligent Management System of Gas Pipeline with Multi-source Data Fusion;Applied Mathematics and Nonlinear Sciences;2024-01-01

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