ANALYSIS OF MEDIUM- AND LONG-TERM CHANGES IN SOLAR RADIATION BASED ON RANDOM FOREST MODEL

Jia Xingbin; Wang Guoju; Wang Renzheng; Gong Xiang

doi:10.19912/j.0254-0096.tynxb.2023-0027

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (5) : 602-610. DOI: 10.19912/j.0254-0096.tynxb.2023-0027

ANALYSIS OF MEDIUM- AND LONG-TERM CHANGES IN SOLAR RADIATION BASED ON RANDOM FOREST MODEL

Jia Xingbin^1,2, Wang Guoju^1,2, Wang Renzheng³, Gong Xiang^1,2

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Abstract

This paper presents a comprehensive analysis of long-term solar radiation trends and influencing factors in Ji’nan City, Shandong Province, based on multi-source radiation observations, using the random forest （RF） algorithm, seasonal autoregressive integrated moving average （SARIMA） model and characteristic importance. The results show that the RF model fits the monthly solar radiation better, with the coefficient of determination and the mean absolute percentage error of 0.92 and 9%, respectively, which are better than the SARIMA model. The monthly solar radiation in Ji’nan City and the surrounding area experiences the process of "darkening" to "brightening" from 1980 to 2020. The maximum temperature and sunshine hours are the main factors affecting the accuracy of the monthly variation of solar radiation, rainfall is an important cause of sudden changes in total monthly solar radiation, and SO₂ and O₃ among atmospheric pollutants have the greatest correlation with solar radiation. This paper is important for guiding the development of the solar energy industry and environmental management in Ji’nan.

Key words

solar radiation / random forest / feature selection / SARIMA model / fitting analysis

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Jia Xingbin, Wang Guoju, Wang Renzheng, Gong Xiang. ANALYSIS OF MEDIUM- AND LONG-TERM CHANGES IN SOLAR RADIATION BASED ON RANDOM FOREST MODEL[J]. Acta Energiae Solaris Sinica. 2024, 45(5): 602-610 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0027

References

[1] 闫云飞, 张智恩, 张力, 等. 太阳能利用技术及其应用[J]. 太阳能学报, 2012, 33(S1): 47-56.
YAN Y F, ZHANG Z E, ZHANG L, et al.Application and utilization technology of solar energy[J]. Acta energiae solaris sinica, 2012, 33(S1): 47-56.
[2] TAHIR Z R, ASIM M.Surface measured solar radiation data and solar energy resource assessment of Pakistan: a review[J]. Renewable and sustainable energy reviews, 2018, 81: 2839-2861.
[3] COSKUN C, OKTAY Z, DINCER I.Estimation of monthly solar radiation distribution for solar energy system analysis[J]. Energy, 2011, 36(2): 1319-1323.
[4] 毛前军, 谢鸣, 帅永, 等. 太阳辐射强度对太阳能腔式吸热器热流密度的影响[J]. 太阳能学报, 2013, 34(10): 1818-1822.
MAO Q J, XIE M, SHUAI Y, et al.Effect of incident solar irradiation on radiation flux distribution of a solar cavity receiver[J]. Acta energiae solaris sinica, 2013, 34(10): 1818-1822.
[5] MYERS D R.Solar radiation modeling and measurements for renewable energy applications: data and model quality[J]. Energy, 2005, 30(9): 1517-1531.
[6] AHMAD M J, TIWARI G N.Solar radiation models-a review[J]. International journal of energy research, 2011, 35(4): 271-290.
[7] BUDYKO M I.The effect of solar radiation variations on the climate of the Earth[J]. Tellus, 1969, 21(5): 611-619.
[8] 齐月, 房世波, 周文佐. 近50年来中国东、西部地面太阳辐射变化及其与大气环境变化的关系[J]. 物理学报, 2015, 64(8): 398-407.
QI Y, FANG S B, ZHOU W Z.Correlative analysis between the changes of surface solar radiation and its relationship with air pollution, as well as meteorological factor in East and West China in recent 50 years[J]. Acta physica sinica, 2015, 64(8): 398-407.
[9] 申彦波, 赵宗慈, 石广玉. 地面太阳辐射的变化、影响因子及其可能的气候效应最新研究进展[J]. 地球科学进展, 2008, 23(9): 915-923.
SHEN Y B, ZHAO Z C, SHI G Y.The progress in variation of surface solar radiation, factors and probable climatic effects[J]. Advances in earth science, 2008, 23(9): 915-923.
[10] 陶求华, 李峥嵘, 蒋福建. 基于气象和空气质量观测数据的日太阳辐射估计[J]. 集美大学学报(自然科学版), 2014, 19(5): 369-374.
TAO Q H, LI Z R, JIANG F J.Estimation of incident daily solar radiation from meteorology and air quality observation[J]. Journal of Jimei University (natural science), 2014, 19(5): 369-374.
[11] 石广玉, 王标, 张华, 等. 大气气溶胶的辐射与气候效应[J]. 大气科学, 2008, 32(4): 826-840.
SHI G Y, WANG B, ZHANG H, et al.The radiative and climatic effects of atmospheric aerosols[J]. Chinese journal of atmospheric sciences, 2008, 32(4): 826-840.
[12] 王建源, 冯建设, 袁爱民. 山东省太阳辐射的计算及其分布[J]. 气象科技, 2006, 34(1): 98-101.
WANG J Y, FENG J S, YUAN A M.Calculation and distributive characteristics of solar radiation in Shandong Province[J]. Meteorological science and technology, 2006, 34(1): 98-101.
[13] MA J Y, LUO Y, SHEN Y B, et al.Solar energy forecasting methods and their applications and problems[J]. Resource science, 2011, 33(5): 829-837.
[14] 马金玉. 中国地面太阳辐射长期变化特征及短期预报方法研究[D]. 南京: 南京信息工程大学, 2011.
MA J Y.The long-term variation and short-term prediction method of surface solar radiation in China[D]. Nanjing: Nanjing University of Information Science & Technology, 2011.
[15] 高阳, 张碧玲, 毛京丽, 等. 基于机器学习的自适应光伏超短期出力预测模型[J]. 电网技术, 2015, 39(2): 307-311.
GAO Y, ZHANG B L, MAO J L, et al.Machine learning-based adaptive very-short-term forecast model for photovoltaic power[J]. Power system technology, 2015, 39(2): 307-311.
[16] 王红睿. 机器学习背景下的太阳辐射数据基本重构方法[C]//中国天文学会2018年学术年会摘要集. 昆明, 中国, 2018: 43.
WANG H R.A fundamental reconstruction method for solar radiation data in the context of machine learning[C]//Abstracts of the 2018 Annual Meeting of the Chinese Astronomical Society. Kunming, China, 2018: 43.
[17] 应王敏, 刘晓洁, 房世峰, 等. 基于机器学习的日尺度短波净辐射气候资源遥感反演研究[J]. 资源科学, 2020, 42(10): 1998-2009.
YING W M, LIU X J, FANG S F, et al.Retrieval of daily net surface shortwave radiation climatic resources based on machine learning[J]. Resources science, 2020, 42(10): 1998-2009.
[18] VOYANT C, NOTTON G, KALOGIROU S, et al.Machine learning methods for solar radiation forecasting: a review[J]. Renewable energy, 2017, 105: 569-582.
[19] AĞBULUT Ü, GÜREL A E, BIÇEN Y. Prediction of daily global solar radiation using different machine learning algorithms: evaluation and comparison[J]. Renewable and sustainable energy reviews, 2021, 135: 110114.
[20] ZHOU Y, LIU Y F, WANG D J, et al.A review on global solar radiation prediction with machine learning models in a comprehensive perspective[J]. Energy conversion and management, 2021, 235: 113960.
[21] FALLAHI S, AMANOLLAHI J, TZANIS C G, et al.Estimating solar radiation using NOAA/AVHRR and ground measurement data[J]. Atmospheric research, 2018, 199: 93-102.
[22] SUN H W, GUI D W, YAN B W, et al.Assessing the potential of random forest method for estimating solar radiation using air pollution index[J]. Energy conversion and management, 2016, 119: 121-129.
[23] BENALI L, NOTTON G, FOUILLOY A, et al.Solar radiation forecasting using artificial neural network and random forest methods: application to normal beam, horizontal diffuse and global components[J]. Renewable energy, 2019, 132: 871-884.
[24] KARASU S, ALTAN A.Recognition model for solar radiation time series based on random forest with feature selection approach[C]//2019 11th International Conference on Electrical and Electronics Engineering (ELECO). Bursa, Turkey, 2020: 8-11.
[25] ALSHARIF M, YOUNES M, KIM J.Time series ARIMA model for prediction of daily and monthly average global solar radiation: the case study of Seoul, South Korea[J]. Symmetry, 2019, 11(2): 240.
[26] BOUALIT S, MELLIT A.SARIMA-SVM hybrid model for the prediction of daily global solar radiation time series[C]//2016 International Renewable and Sustainable Energy Conference(IRSEC). IEEE, Marrakech, Morocco, 2016:712-717.
[27] 丁一汇, 李巧萍, 柳艳菊, 等. 空气污染与气候变化[J]. 气象, 2009, 35(3): 3-14, 129.
DING Y H, LI Q P, LIU Y J, et al.Atmospheric aerosols, air pollution and climate change[J]. Meteorological monthly, 2009, 35(3): 3-14, 129.
[28] BRISTOW K L, CAMPBELL G S.On the relationship between incoming solar radiation and daily maximum and minimum temperature[J]. Agricultural and forest meteorology, 1984, 31(2): 159-166.
[29] SAMANI Z.Estimating solar radiation and evapotranspiration using minimum climatological data[J]. Journal of irrigation and drainage engineering, 2000, 126(4): 265-267.
[30] BAKIRCI K.Models of solar radiation with hours of bright sunshine: a review[J]. Renewable and sustainable energy reviews, 2009, 13(9): 2580-2588.
[31] DÍAZ-TORRES J J, HERNÁNDEZ-MENA L, MURILLO-TOVAR M A, et al. Assessment of the modulation effect of rainfall on solar radiation availability at the Earth’s surface[J]. Meteorological applications, 2017, 24(2): 180-190.
[32] TANU M, AMPONSAH W, YAHAYA B, et al.Evaluation of global solar radiation, cloudiness index and sky view factor as potential indicators of Ghana’s solar energy resource[J]. Scientific African, 2021, 14: e01061.
[33] 张亮, 王赤, 傅绥燕. 太阳活动与全球气候变化[J]. 空间科学学报, 2011, 31(5): 549-566.
ZHANG L, WANG C, FU S Y.Solar variation and global climate change[J]. Chinese journal of space science, 2011, 31(5): 549-566.
[34] KHODAKARAMI J, GHOBADI P.Urban pollution and solar radiation impacts[J]. Renewable and sustainable energy reviews, 2016, 57: 965-976.
[35] 薛德强. 济南的城市发展对气候的影响[J]. 气象, 1996, 22(2): 3-6.
XUE D Q.Effects of development of Ji’nan City on climate[J]. Meteorological monthly, 1996, 22(2): 3-6.
[36] 王建源, 赵玉金, 陈艳春, 等. 山东省太阳辐射及其光热生产潜力评估[J]. 安徽农业科学, 2010, 38(7): 3581-3583, 3585.
WANG J Y, ZHAO Y J, CHEN Y C, et al.Evaluation on solar radiation resource and photosynthetic and thermal potential productivity in Shandong Province[J]. Journal of Anhui agricultural sciences, 2010, 38(7): 3581-3583, 3585.
[37] 桑博, 孙明虎. 济南市大气中SO₂浓度变化特征研究[J]. 中国环境管理干部学院学报, 2017, 27(4): 78-81.
SANG B, SUN M H.A study on concentration variation of atmospheric SO₂ in Jinan[J]. Journal of Environmental Management College of China, 2017, 27(4): 78-81.
[38] 曾贤刚, 阮芳芳, 姜艺婧. 中国臭氧污染的空间分布和健康效应[J]. 中国环境科学, 2019, 39(9): 4025-4032.
ZENG X G, RUAN F F, JIANG Y J.Spatial distribution and health effects of ozone pollution in China[J]. China environmental science, 2019, 39(9): 4025-4032.
[39] JAMALY M, KLEISSL J.Spatiotemporal interpolation and forecast of irradiance data using Kriging[J]. Solar energy, 2017, 158: 407-423.
[40] 杨凌霄, 侯鲁健, 吕波, 等. 济南市大气细颗粒物水溶性组分及大气传输的研究[J]. 山东大学学报(工学版), 2007, 37(4): 98-103.
YANG L X, HOU L J, LYU B, et al.Study on the water-soluble ions in fine particle matter and the long-range transport of air masses in the city of Ji’nan[J]. Journal of Shandong University (engineering science), 2007, 37(4): 98-103.
[41] 沈志宝, 王尧奇, 季国良, 等. 太阳辐射在山谷城市污染大气中的削弱[J]. 高原气象, 1982, 1(4): 74-83.
SHEN Z B, WANG Y Q, JI G L, et al.The attenuation of solar radiation in the polluted urban atmosphere[J]. Plateau meteorology, 1982, 1(4): 74-83.