引用本文:段旭,王志强,马军,韩路,赵晓理,宫敬. 河北省供暖季天然气负荷与气温关系分析研究[J]. 石油与天然气化工, 2019, 48(5): 42-48.
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河北省供暖季天然气负荷与气温关系分析研究
段旭1,王志强2,马军2,韩路2,赵晓理2,宫敬1
1.中国石油大学(北京)油气管道输送安全国家工程实验室/石油工程教育部重点实验室/ 城市油气输配技术北京市重点实验室 ;2.中国石油天然气销售北方公司
摘要:
气温是影响供暖季天然气负荷的关键因素。基于河北省地区供暖季日用气量及气温的历史数据,比较了日用气量与日平均温度、最高温度和最低温度的相关程度,建立一元及二元回归方程,能够实现对没有较大政策变化下的供暖季的用气量预测,分析结果表明,二元预测的误差较小。同时考虑了气温累积效应对供暖季用气量的影响,根据日气温的不同情况选取不同的气温累积效应系数对温度进行修正,提高了预测的准确性。分析供暖季天然气负荷与气温的关系,为更准确地预测天然气负荷提供了参考。
关键词:  天然气负荷  气温  回归分析  气温累积效应  供暖季
DOI:10.3969/j.issn.1007-3426.2019.05.009
分类号:
基金项目:“十三五”国家科技重大专项专题“多气合采全开发周期集输及处理工艺”(2016ZX05066005-001)
Analysis of relationship between natural gas load and air temperature in heating season in Hebei Province
Duan Xu1, Wang Zhiqiang2, Ma Jun2, Han Lu2, Zhao Xiaoli2, Gong Jing1
1. China University of Petroleum (Beijing)/National Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, Beijing, China;2. North Branch Natural Gas Marketing Company, Beijing, China
Abstract:
Air temperature is a key factor affecting the natural gas load in the heating season. Based on the historical data of daily gas consumption and air temperature in the heating season in Hebei Province, the correlation degree is compared by calculating the correlation coefficient between the gas consumption and the daily average air temperature, maximum air temperature and minimum air temperature. The regression analysis and binary regression analysis are performed respectively.Regression equation is obtained to predict the gas consumption in the next heating season without major policy changes. By comparison, the fitting and forecasting results of the binary regression are better. Considering the influence of the accumulation effect of air temperature on the gas consumption in the heating season, the temperature is corrected by using different air temperature accumulation effect coefficients selected according to the different daily air temperature. The calculation results show that the accuracy is improved after temperature is corrected. In general, this study provides a reference for more accurate prediction of natural gas load by analyzing the relationship between natural gas load and air temperature during the heating season.
Key words:  natural gas load  air temperature  regression analysis  accumulative effect of temperature  heating season