基于最大熵法和ARMA模型的中国电力需求波动和拐点预测

Lizi Zhang, Limei Xu
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引用次数: 3

摘要

受经济周期的影响,中国电力需求呈现出一定的周期性波动,这对国民经济的发展和电力行业的生产效率都是不利的。正确预测中国电力需求的波动规律和拐点,有助于制定符合周期的相应策略。在充分考虑电力需求波动的情况下,本文建立了基于最大熵法和ARMA模型的预测模型:首先对电力需求增长率进行频谱分析,得到周期波动的主要周期,然后通过最小二乘法采用能反映波动特征的周期函数;其次,建立了残差序列的ARMA模型,残差序列通过从原始序列中剔除周期序列得到;最后,将周期函数与ARMA模型相结合,得到混合预测模型。实验结果表明,该模型是有效、合理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting of fluctuations and turning points of power demand in China based on the maximum entropy method and ARMA model
Influenced by the economic cycle, power demand in china shows some cyclical fluctuations, which is unhealthy for the development of national economy and production efficiency of electric power industry. Correctly forecasting the fluctuation rule of power demand and the turning points in China is helpful to make the corresponding strategy complied with the cycle. With the full consideration of power demand fluctuations, the paper establishes a forecasting model based on maximum entropy method and ARMA model: firstly, the paper makes a spectrum analysis on the growth rate of power demand and the major cycle of the cyclical fluctuations can be correspondingly obtained, then a periodic function which can reflect the fluctuation features is employed through the least square method; secondly, the paper establishes an ARMA model on the residual series which can be obtained by eliminating the periodic sequence from the original series; at last, the hybrid forecasting model is obtained by combining the periodic function and ARMA model. Experimental results show that the proposed model is effective and reasonable.
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