Forecasting the natural gas demand in China using a self-adapting intelligent grey model
Forecasting the natural gas demand in China using a self-adapting intelligent grey model
复制标题
利用自适应智能灰色模型预测中国天然气需求
DOI：
10.1016/j.energy.2016.06.090
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发表时间：
2016-10
期刊：
影响因子：
9
通讯作者：
Li, Chuan
中科院分区：
文献类型：
--
作者：
Zeng, Bo;Li, Chuan
合理预测我国天然气需求量对政府制定能源政策、调整产业结构具有重要意义。为此，本文提出了一种自适应智能灰色预测模型。与传统灰色模型固有的结构固定、适应性差的缺点相比，该模型能根据建模序列的真实的数据特征自动优化模型参数。本研究分别采用所提出的新模型--离散灰色模型、偶差灰色模型和经典灰色模型对中国2002-2010年天然气需求进行模拟，并对2011-2014年天然气需求进行预测。结果表明，新模型具有最佳的模拟和预测精度。最后，利用新模型对2015-2020年中国天然气需求进行了预测。预测显示，未来六年需求将迅速增长。因此，为了保持未来天然气的供需平衡，中国政府需要采取一些措施，如从国外大量进口天然气，增加国内产量，使用更多的替代能源，减少工业对天然气的依赖。
Reasonably forecasting demands of natural gas in China is of significance as it could aid Chinese government in formulating energy policies and adjusting industrial structures. To this end, a self-adapting intelligent grey prediction model is proposed in this paper. Compared with conventional grey models which have the inherent drawbacks of fixed structure and poor adaptability, the proposed new model can automatically optimize model parameters according to the real data characteristics of modeling sequence. In this study, the proposed new model, discrete grey model, even difference grey model and classical grey model were employed, respectively, to simulate China's natural gas demands during 2002–2010 and forecast demands during 2011–2014. The results show the new model has the best simulative and predictive precision. Finally, the new model is used to forecast China's natural gas demand during 2015–2020. The forecast shows the demand will grow rapidly over the next six years. Therefore, in order to maintain the balance between the supplies and the demands for the natural gas in the future, Chinese government needs to take some measures, such as importing huge amounts of natural gas from abroad, increasing the domestic yield, using more alternative energy, and reducing the industrial reliance on natural gas.
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