Influence of load characteristic on economic operation of LNG receiving terminal

CHEN Taoqiang; LI Ning; WEI Guanghua; GAO Yifeng; LIU Ben; HUANGFU Lixia; GUO Kaihua

doi:10.11949/j.issn.0438-1157.20181126

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Influence of load characteristic on economic operation of LNG receiving terminal

更新时间：2025-12-10

- Influence of load characteristic on economic operation of LNG receiving terminal
- CIESC Journal Issue S2, Pages: 436-441(2018)
- 作者机构：
  
  1. 中山大学智能工程学院,广东,广州,512500
  2. 广东大鹏液化天然气有限公司,广东,深圳,518000
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20181126
  CLC： E08
- Online First：31 December 2018，
  
  Published：31 December 2018
- 稿件说明：
移动端阅览
CHEN Taoqiang, LI Ning, WEI Guanghua, et al. Influence of load characteristic on economic operation of LNG receiving terminal[J]. CIESC Journal, 2018, (S2): 436-441.
DOI：

CHEN Taoqiang, LI Ning, WEI Guanghua, et al. Influence of load characteristic on economic operation of LNG receiving terminal[J]. CIESC Journal, 2018, (S2): 436-441. DOI： 10.11949/j.issn.0438-1157.20181126.

摘要

对于特定的燃气管网和接收站设备环境，接收站的运行策略取决于其负荷特性，研究各种负荷条件下的最优运行方案对节能增效有重要意义。基于日负荷周期性和两部制峰谷电价建立了优化数学模型，并导出普适性优化准则，且结合动态仿真系统获得三种典型工况的优化方案，并以此得出普适性的日、月最优运行方案。通过对现场真实数据的分析导出用户负荷特性曲线方程，从而便于任何日负荷的寻优。计算表明，优化运行方案较现场运行策略成本日最高可节省12%。按夏季典型月负荷分布，优化运行方案较现场运行方案成本每月可节省6.3%。

Abstract

For a specific environment gas pipe network and terminal equipment

the operation of the terminal strategy depends on the load characteristics. Study on the best operating strategy of different load characteristics has a great significance to energy-saving. Based on the periodicity of daily load and peak and valley price

the optimization mathematical model is established and the universal optimization criterion is derived. In addition

the optimization scheme of three typical working conditions is obtained with the dynamic simulation system

and also the universal optimal operation scheme of day and month is obtained. The load characteristic curve equation is derived by analyzing the field data

which allows of the optimization of each kinds of load characteristic. The calculation shows that the optimal operation scheme can save up to 12% of the daily cost compared with the on-site operation strategy. According to the typical monthly load distribution in summer

the optimal scheme can save 6.3% per month compared with the on-site strategy.

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