基于灰色-ARIMA耦合模型的中国发电量短期预测
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Short-term Power Generation Forecasting in China Based on Gray-ARIMA Coupling Model
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    摘要:

    针对国内发电量的持续增长现象,基于中国2012—2021年的发电量数据,使用新陈代谢GM(1,1)模型与阻尼趋势模型耦合所得的灰色- ARIMA耦合模型,对中国2022—2030年的短期发电量进行预测。比较新陈代谢GM(1,1)、传统GM(1,1)与新信息GM(1,1) 模型的试验结果,将误差平方和最小的模型与ARIMA模型耦合,引入时间序列分析来拟合发电量,构建等权的灰色-ARIMA耦合预测模型,得到2022—2030年发电量的可靠耦合预测数据,具有一定的鲁棒性。为我国制定新能源措施和发展规划,实现碳中和、碳达峰及可持续发展具有重要的借鉴意义。

    Abstract:

    In view of the continuous growth of China's electricity generation, based on China's electricity generation data from 2012 to 2021, the short-term electricity generation of China from 2022 to 2030 is predicted by using the gray-arima coupling model, which is derived from the metabolic GM(1,1) model and the damped trend model.?By comparing the experimental results of metabolic GM(1,1), traditional GM(1,1) and new information GM(1,1) models.The SSE minimum model is coupled with ARIMA model, and time series analysis is introduced to fit the power generation.An equal-weight gray-arima coupling prediction model is constructed.?The reliable coupling prediction data of power generation from 2022 to 2030 is obtained, which has certain robustness.?It has important reference significance for China to formulate new energy measures and development plans to achieve carbon neutrality, carbon peak and sustainable development.

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周彬彬,黄嘉昕,耿冉冉,尹新然,徐宝靖.基于灰色-ARIMA耦合模型的中国发电量短期预测[J].科技与产业,2022,22(12):382-387

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  • 在线发布日期: 2022-12-30