基于时间序列疏系数模型的太阳辐射年际变化趋势预测

doi:10.3976/j.issn.1002-4026.2023.01.015

Abstract

Abstract:

In this paper, we have used the observed data of annual total solar radiation from 1961 to 2016 in Jinan, Shandong Province, and compared and analyzed the fitting results of time series models AR(5) and ARIMA((1,2,4),1,0) via model identification and statistical tests. As per the residual test results, the sparse coefficient model ARIMA((1,2,4),1,0) can be used to predict the total annual surface solar radiation. The prediction results show that the overall interannual variation of surface solar radiation in Jinan from 2017 to 2025 follows an increasing trend and the utilization of solar energy resources can be further explored. Compared to the results of the multiple linear regression model, the time series sparse coefficient model has less error and higher prediction accuracy.

Key words: total annual solar radiation, time series analysis, ARIMA sparsity coefficient model, interannual variability, trend prediction, model comparison

CLC Number:

TK511

JIA Xingbin, GONG Xiang. Predicting interannual variation of global solar radiation trends in Jinan City based on time series sparse coefficient model[J].Shandong Science, 2023, 36(1): 115-123.

Figures/Tables 11

Fig.1

Table 1

ADF unit root test"

类型	滞后阶数	模型具体结构	差分前		差分后
类型	滞后阶数	模型具体结构	τ	P	τ	P
零均值	0	$x t = ε t, ε t N ~ 0, σ ε 2$	-0.48	0.50	-9.53	<0.001
	1	$x t = φ 1 x t - 1 + ε t, ε t ~ N 0, σ ε 2$	-0.53	0.48	-8.09	<0.001
单均值	0	$x t = μ + ε t, ε t ~ N 0, σ ε 2$	-3.83	<0.01	-9.46	<0.001
	1	$x t = μ + φ 1 x t - 1 + ε t, ε t ~ N 0, σ ε 2$	-3.28	0.02	-8.04	<0.001
趋势	0	$x t = μ + β t + ε t, ε t ~ N 0, σ ε 2$	-4.25	<0.01	-9.38	<0.001
	1	$x t = μ + β t + φ 1 x t - 1 + ε t, ε t ~ N 0, σ ε 2$	-3.55	0.04	-8.04	<0.001

Table 1

Fig.2

Table 2

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Table 3

Table 4

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Fig.7

References 28

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延迟期数	差分前		差分后
延迟期数	L	P	L	P
6	52.93	<0.000 1	23.43	<0.001
12	59.79	<0.000 1	29.18	<0.001

参数	参数显著性检验				残差白噪声检验
	AR(5)		ARIMA(4,1,0)		AR(5)		ARIMA(4,1,0)
	T	P	T	P	T	P	T	P
μ	29.53	<0.000 1	-0.37	0.071
φ₁	4.73	<0.000 1	-2.54	0.014			3.14	0.37
φ₂	-1.22	0.229 4	-3.65	<0.001	1.37	0.24	5.94	0.75
φ₃	2.24	0.029 8	-1.00	0.321	4.35	0.73	6.82	0.96
φ₄	-2.33	0.023 8	-3.74	<0.001	5.82	0.95	15.11	0.82
φ₅	3.44	0.001 2			12.24	0.88

参数	估计	标准误差	T	P	滞后
AR(1, 1)	-0.29	0.12	-2.35	0.023	1
AR(1, 2)	-0.44	0.12	-3.63	<0.001	2
AR(1, 4)	-0.45	0.12	-3.65	<0.001	4

Predicting interannual variation of global solar radiation trends in Jinan City based on time series sparse coefficient model

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