基于EMD与BP神经网络的北京市采暖季天然气消耗量预测  

Forecast of Natural Gas Consumption in Heating Season Based on EMD and BP Neural Network Methods in Beijing

作　　者：闵晶晶 王华 董颜 MIN Jingjing;WANG Hua;DONG Yan(Beijing Meteorological Service Center,Beijing 100097,China)

机构地区：[1]北京市气象服务中心,北京100097

出　　处：《干旱气象》2021年第5期864-870,共7页Journal of Arid Meteorology

基　　金：国家重点研发计划“科技冬奥”重点专项项目“冬奥会气象条件预测保障关键技术”(2018YFF0300100)第5课题(2018YFF0300105)资助。

摘　　要：基于2002—2018年北京市采暖季天然气消耗量和地面常规气象观测资料以及社会统计年度资料,采用经验模态分解、相关分析等方法分析北京地区采暖季天然气消耗量的年际变化特征及影响要素。在此基础上,利用BP神经网络方法构建采暖季天然气消耗量预测模型,并对模型进行评估检验。结果表明:(1)近17 a北京市采暖季天然气消耗量呈现持续增加趋势,经验模态分解方法能够较好地分离出天然气的社会消耗量和气象消耗量,分别反映了天然气消耗量的长期变化趋势和短期波动特征。(2)采暖季天然气的社会消耗量与GDP、集中供热面积和常住人口数量呈显著正相关;气象消耗量与气温和负积温呈显著负相关,而与降水量和持续低温日数呈显著正相关,当采暖季气温明显偏低或出现较强降雪、持续低温等天气过程时,天然气的气象消耗量将大幅增加。(3)北京市采暖季天然气消耗量EMD_BP预测模型具有较好的预测效果,平均相对误差为5.6%,能够准确预测天然气气象消耗量的峰谷变化。Based on natural gas consumption,ground conventional meteorological observation data in Beijing in heating season from 2002 to 2018,as well as yearly social statistical information,the inter-annual variation characteristics of natural gas consumption in heating season in Beijing and its impact factors were analyzed by using empirical mode decomposition(EMD)and correlation analysis methods.And on this basis the forecast model of natural gas consumption in heating season was established by using back propagation(BP)neural network method,further the model was tested and evaluated.The results are as follows:(1)The natural gas consumption increased persistently in heating season from 2002 to 2018 in Beijing,and it was decomposed better into social and meteorological consumptions by EMD,which reflected long-term variation trend and short-term fluctuation of natural gas consumption,respectively.(2)The social consumption of natural gas in heating season had significantly positive correlation with GDP,intensive heating supply area and resident population number in Beijing.The meteorological consumption had significantly negative correlation with air temperature and negative accumulative temperature,while it was significantly positive correlated with precipitation and persistent low-temperature days.In heating season,when the air temperature was obviously lower or the continuous low-temperature and strong snowfall processes appeared,the meteorological consumption of natural gas would increase sharply.(3)The forecast model of gas consumption in heating season based on EMD_BP method had better prediction effect in Beijing,the average relative error was 5.6%,especially the model could predict accurately the peak and valley change of meteorological consumption of gas,which could provide scientific reference to a certain extent for energy planning and regulating.

关 键 词：经验模态分解 BP神经网络 采暖季 天然气消耗量 预测模型 

分 类 号：P49[天文地球—大气科学及气象学] TU996[建筑科学—供热、供燃气、通风及空调工程]