基于大数据的地下储气库冬季调峰优化运行研究
Research on peak-shaving optimization for underground gas storage in winter based on big data
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- 引用格式:
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徐俊杰,张崇玮,汪岩,许明.基于大数据的地下储气库冬季调峰优化运行研究[J].天然气与石油,2021,39(6):1-6.doi:10.3969/j.issn.1006-5539.2021.06.001
XU Junjie, ZHANG Chongwei, WANG Yan, XU Ming.Research on peak-shaving optimization for underground gas storage in winter based on big data[J].Natural Gas and Oil,2021,39(6):1-6.doi:10.3969/j.issn.1006-5539.2021.06.001
- DOI:
- 10.3969/j.issn.1006-5539.2021.06.001
- 作者:
- 徐俊杰 张崇玮 汪岩 许明
XU Junjie, ZHANG Chongwei, WANG Yan, XU Ming
- 作者单位:
- 国家管网集团北京管道有限公司, 北京 100101
PipeChina Beijing Gas Pipeline Co., Ltd., Beijing, 100101, China
- 关键词:
- 大数据;地下储气库;冬季调峰;运行研究
Big data; Underground gas storage(UGS); Peakshaving in winter; Operation research
- 摘要:
L储气库群是国内运行最早的大型商业储气库群,主要保障京津冀地区冬季调峰供气需求。由于京津冀地区冬季用气明显受平均气温、节假日等因素影响,导致冬季不同月份、每月中不同日期的用气量变化较大,面临科学合理安排地下储气库群运行生产的问题。为此,利用储气库采气生产大数据平台,结合L储气库群多周期冬季调峰运行动态,分析了各储气库生产运行特征,评价了储气库不同压力对应的调峰采气能力,首次建立了京津冀地区储气库冬季采气调峰模型,并以此制定了储气库采气调峰方案,指导L储气库群科学合理运行。基于大数据的采气调峰模型可为国内同类储气库冬季调峰采气优化运行提供科学指导。
The L gas storage groups are the earliest commercial large-scale gas storage groups operating in China, which mainly guarantee peak-shaving gas supply demand in the capital city and surrounding areas in winter. Because the winter gas consumption in the region is obviously affected by the factors such as average temperature, holidays and so on, the gas consumption varies greatly in different months and on different days in winter. It is a big challenge to scientifically and rationally operate and manage the underground gas storage groups. Therefore based on the big data platform of gas storage production and combined with the multi-period peak shaving operation in winter of L gas storage groups, the research team analyses the production and operation characteristics of each gas storage, evaluates the peak-shaving gas production capacity corresponding to different pressures of the underground gas storage. This research establishes the winter peak-shaving model of gas production from gas storages in Beijing-Tianjin area for the first time, and on that basis formulates gas storages peak-shaving scheme to guide the scientific and rational operation of L gas storage groups. The gas production peak-shaving model based on big data can provide scientific guidance for the optimization of peak-shaving gas production for domestic gas storages of the same nature in winter.