基于灰色模型的中国天然气海上进口需求量预测
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摘要
天然气作为清洁能源,在中国经济可持续发展中发挥着重要作用。2017年中国天然气消费量突破2300×10~8m~3,增量超过330×10~8m~3,同比增幅达到17%,刷新了中国天然气消费增量的历史纪录,打破了原有天然气市场的供需平衡。为了满足天然气需求,需要扩大海上天然气进口。准确预测未来天然气海上进口需求量对能源战略制定、沿海储气设施建设及煤改气计划推进有重要意义。为预测中国天然气海上进口需求量,基于中国2006-2017年天然气海上进口量数据,建立GM(1,1)、两次拟合GM(1,1)和GVM(1,1)预测模型并进行精度检验。检验结果表明,GM(1,1)和两次拟合GM(1,1)预测模型拥有较好的预测精度,能很好地适应中国天然气海上进口量数据的非线性增长特征模式。通过GM(1,1)和两次拟合GM(1,1)模型预测中国2018-2020年天然气海上进口需求量,结果显示:2019年底中国海上天然气进口量将有望突破700×10~8m~3,2020年底将超过840×10~8m~3,年均增幅将超过21%。结论认为,确保天然气进口渠道多元化可有效保障天然气供应安全,期间不断增长的天然气海上进口需求量将对中国沿海接收、储存气设施的规划和布置提出更高的要求。
As one of clean energy, natural gas plays an important role in the sustainable economic development of our country. According to relevant data, China's natural gas consumption exceeded 2300×10~8m~3 in 2017, with an increase of more than 330×10~8m~3, increasing 17% over the same period last year, which broke the history of China's natural gas consumption increment and the balance between supply and demand in the original natural gas market. In order to meet the demand for natural gas, it is necessary to expand offshore natural gas imports. It is of great significance to accurately predict the future import demand of natural gas on the sea for the formulation of energy strategy, the construction of coastal gas storage facilities and the promotion of the plan of coal conversion to gas. In order to predict China's natural gas import demand at sea, based on the data of China's natural gas import volume from 2006 to 2017, the prediction models of GM(1,1),twice fitting GM(1,1) and GVM(1,1) was established, and their accuracy was tested. The test results show that, the prediction models has good prediction accuracy, and can well adapt to the nonlinear growth model of China's natural gas import data on the sea. The GM(1,1) and twice fitting GM(1,1) models are used to forecast China's natural gas import demand from 2018 to 2020. The results show that the amount of offshore natural gas import will reach 580×10~8m~3 at the end of 2018 and 700×10~8m~3 at the end of 2019. By the end of 2020, it will exceed 840×10~8m~3, with an average annual growth rate of more than 21%. The conclusion is that the diversification of natural gas import channels can effectively ensure the safety of natural gas supply. The increasing demand for natural gas imports on the sea during this period will put forward higher requirements for the planning and layout of the facilities for receiving and storing gas along the coast of China.
As one of clean energy, natural gas plays an important role in the sustainable economic development of our country. According to relevant data, China's natural gas consumption exceeded 2300×10~8m~3 in 2017, with an increase of more than 330×10~8m~3, increasing 17% over the same period last year, which broke the history of China's natural gas consumption increment and the balance between supply and demand in the original natural gas market. In order to meet the demand for natural gas, it is necessary to expand offshore natural gas imports. It is of great significance to accurately predict the future import demand of natural gas on the sea for the formulation of energy strategy, the construction of coastal gas storage facilities and the promotion of the plan of coal conversion to gas. In order to predict China's natural gas import demand at sea, based on the data of China's natural gas import volume from 2006 to 2017, the prediction models of GM(1,1),twice fitting GM(1,1) and GVM(1,1) was established, and their accuracy was tested. The test results show that, the prediction models has good prediction accuracy, and can well adapt to the nonlinear growth model of China's natural gas import data on the sea. The GM(1,1) and twice fitting GM(1,1) models are used to forecast China's natural gas import demand from 2018 to 2020. The results show that the amount of offshore natural gas import will reach 580×10~8m~3 at the end of 2018 and 700×10~8m~3 at the end of 2019. By the end of 2020, it will exceed 840×10~8m~3, with an average annual growth rate of more than 21%. The conclusion is that the diversification of natural gas import channels can effectively ensure the safety of natural gas supply. The increasing demand for natural gas imports on the sea during this period will put forward higher requirements for the planning and layout of the facilities for receiving and storing gas along the coast of China.
引文
[1]江河,陈建荣.放宽准入完善机制加强监管:2017年中国油气政策综述[J].国际石油经济,2018(2):15-21.
[2]李文华.新时期国家能源发展战略问题研究[D].天津:南开大学,2013.
[3]范文科,张福东,王宗礼,等.中国石油“十一五”天然气勘探新进展与未来大气田勘探新领域分析[J].中国石油勘探,2012,17(1):8-13.
[4]袭明.中国天然气地下储气库现状及发展趋势[J].石化技术,2017,24(8):190.
[5]孙文.2017年全球液化天然气市场回顾与展望[J].国际石油经济,2018(4):46-52.
[6]陆家亮.进口气源多元化是保障我国天然气长期供应安全的关键[J].天然气工业,2010,30(11):4-9.
[7]潘月星,赵军.中国液化天然气(LNG)进口贸易发展的新问题与新举措[J].对外经贸实务,2018(4):48-51.
[8]穆献中,李国昊.基于系统动力学模型的中国天然气需求情景预测及影响因素研究[J].工程研究-跨学科视野中的工程,2018(1):56-67.
[9]胡小夫,易梓仪,肖克勤.我国天然气市场消费量预测与发展趋势研究[J].天然气技术与经济,2016,10(2):57-60,83.
[10]Shaikh F,Ji Q,Shaikh P H,et al.Forecasting China’s natural gas demand based on optimized nonlinear grey models[J].Energy,2017(140):941-951.
[11]张学龙,王云峰,谢廷宇.灰色预测模型在石油化工原料价格预测中的应用[J].数学的实践与认识,2014,44(16):31-38.
[12]张卫冰.一种灰色非齐次天然气需求量预测模型的构建[J].油气储运,2015,34(3):288-292.
[13]Lin C S,Liou F M,Huang C P.Grey forecasting model for CO2emissions:A Taiwan study[J].Applied Energy,2011,88(11):3 816-3 820.
[14]Pao H T,Fu H C,Tseng C L.Forecasting of CO2 emissions,energy consumption and economic growth in China using an improved grey model[J].Energy,2012,40(1):400-409.
[15]Wang C N,Phan V T.An Improved Grey Forecasting Models:Case in China’s Coal Consumption Demand[M]//Computational Collective Intelligence.Cham:Springer,2015:544-553.
[16]Kayacan E,Ulutas B,Kaynak O.Grey system theorybased models in time series prediction[J].Expert systems with applications,2010,37(2):1 784-1 789.
[17]罗志鹏.靖西天然气管道负荷预测研究[D].西安:西安石油大学,2012.
[2]李文华.新时期国家能源发展战略问题研究[D].天津:南开大学,2013.
[3]范文科,张福东,王宗礼,等.中国石油“十一五”天然气勘探新进展与未来大气田勘探新领域分析[J].中国石油勘探,2012,17(1):8-13.
[4]袭明.中国天然气地下储气库现状及发展趋势[J].石化技术,2017,24(8):190.
[5]孙文.2017年全球液化天然气市场回顾与展望[J].国际石油经济,2018(4):46-52.
[6]陆家亮.进口气源多元化是保障我国天然气长期供应安全的关键[J].天然气工业,2010,30(11):4-9.
[7]潘月星,赵军.中国液化天然气(LNG)进口贸易发展的新问题与新举措[J].对外经贸实务,2018(4):48-51.
[8]穆献中,李国昊.基于系统动力学模型的中国天然气需求情景预测及影响因素研究[J].工程研究-跨学科视野中的工程,2018(1):56-67.
[9]胡小夫,易梓仪,肖克勤.我国天然气市场消费量预测与发展趋势研究[J].天然气技术与经济,2016,10(2):57-60,83.
[10]Shaikh F,Ji Q,Shaikh P H,et al.Forecasting China’s natural gas demand based on optimized nonlinear grey models[J].Energy,2017(140):941-951.
[11]张学龙,王云峰,谢廷宇.灰色预测模型在石油化工原料价格预测中的应用[J].数学的实践与认识,2014,44(16):31-38.
[12]张卫冰.一种灰色非齐次天然气需求量预测模型的构建[J].油气储运,2015,34(3):288-292.
[13]Lin C S,Liou F M,Huang C P.Grey forecasting model for CO2emissions:A Taiwan study[J].Applied Energy,2011,88(11):3 816-3 820.
[14]Pao H T,Fu H C,Tseng C L.Forecasting of CO2 emissions,energy consumption and economic growth in China using an improved grey model[J].Energy,2012,40(1):400-409.
[15]Wang C N,Phan V T.An Improved Grey Forecasting Models:Case in China’s Coal Consumption Demand[M]//Computational Collective Intelligence.Cham:Springer,2015:544-553.
[16]Kayacan E,Ulutas B,Kaynak O.Grey system theorybased models in time series prediction[J].Expert systems with applications,2010,37(2):1 784-1 789.
[17]罗志鹏.靖西天然气管道负荷预测研究[D].西安:西安石油大学,2012.