青岛地区四季天气对光伏发电量的影响
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摘要
基于青岛大学自建分布式光伏并网电站的实际运行情况,研究青岛地区四季天气对光伏发电量的影响。对电站发电量及环境因素等数据进行筛选和统计,分析造成不同季节发电量差异的原因。主要对光照强度、温度及相对湿度这3个因素对光伏电站发电功率的影响程度进行解耦分析,研究青岛沿海地区特有气象对光伏发电系统输出功率的影响。该研究可为青岛及气候相似地区的光伏产业发展提供数据参考。
On the basis of actual operating conditions of the self-built distributed photovoltaic grid-connected power station of Qingdao university, this paper studies influence of weathers in the four seasons on photovoltaic power generation in Qingdao. By data screening and statistics about power generating capacity and environmental factors of the power station, it analyzes reasons for causing differences of generating capacity in the four seasons. It mainly makes decoupling analysis of incidence of three factors including illumination intensity, temperature and relative humidity on generated power of the photovoltaic station and studies effect of specific weathers in the coastal areas of Qingdao on output power of the photovoltaic generating system. The study can provide data references for development of photovoltaic industries in Qingdao and other areas with similar climates.
On the basis of actual operating conditions of the self-built distributed photovoltaic grid-connected power station of Qingdao university, this paper studies influence of weathers in the four seasons on photovoltaic power generation in Qingdao. By data screening and statistics about power generating capacity and environmental factors of the power station, it analyzes reasons for causing differences of generating capacity in the four seasons. It mainly makes decoupling analysis of incidence of three factors including illumination intensity, temperature and relative humidity on generated power of the photovoltaic station and studies effect of specific weathers in the coastal areas of Qingdao on output power of the photovoltaic generating system. The study can provide data references for development of photovoltaic industries in Qingdao and other areas with similar climates.
引文
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[15] 朱红路,李旭,姚建曦,等.基于小波分析与神经网络的光伏电站功率预测方法[J].太阳能学报,2015,36(11):2725-2730.ZHU Honglu,LI Xu,YAO Jianxi,et al.A power forecasting method for photovoltaic power plant based on wavelet analysis and neural network[J].Acta Energia Sinica,2015,36(11):2725-2730.
[16] 朱琳琳,钟志峰,严海,等.一种新的光伏发电预测模型设计[J].太阳能学报,2016,37(1):63-68.ZHU Linlin,ZHONG Zhifeng,YAN Hai,et al.A new design of photovoltaic power generation forecasting model[J].Acta Energiae Solaris Sinica,2016,37(1):63-68.
[17] 李伟,王冰,陈献慧,等.基于气象因子权重相似日的短期光伏功率预测[J].广东电力,2018(4):59-64.LI Wei,WANG Bing,CHEN Xianhui,et al.Prediction on short-term photovoltaic power based on similar day with meteorological factor weight[J].Guangdong Electric Power,2018(4):59-64.
[18] 杨秋霞,刘同心,高辰,等.计及光伏电站功率越策的电力系统优化分析[J].电力系统保护与控制,2018,46(2):117-123.YANG Qiuxia,LIU Tongxin,GAO Chen,et al.Optimization analysis of power system considering power forecast of photovoltaic power plant[J].Power System Protection and Control,2018,46(2):117-123.
[19] LIU Y ,LI Z ,BAI K ,et al.Short-term power-forecasting method of distributed PV power system for consideration of its effects on load forecasting[J].The Journal of Engineering,2017,2017(13):865-869.
[20] GOLESTANEH F,PINSON P,GOOI H B.Very short-term nonparametric probabilistic forecasting of renewable energy generation-with application to solar energy[J].IEEE Transactions on Power Systems,2016,31(5):3850-3863.
[21] BRACALE A,CARPINELLI G,FALCO P D.A probabilistic competitive ensemble method for short-term photovoltaic power forecasting[J].IEEE Transactions on Sustainable Energy,2017,8(2):551-560.
[22] SALEH M,MEEK L,MASOUM M A S,et al.Battery-less short-term smoothing of photovoltaic generation using sky camera[J].IEEE Transactions on Industrial Informatics,2018,14(2):403-414.
[2] SINHA P,HAYES W,LITTMANN B,et al.Environmental variables affecting solar photovoltaic energy generation in Morocco[C]//2014 International Renewable and Sustainable Energy Conference (IRSEC).Ouarzazate:IRSEC,2014:230-234.
[3] GUO B,JAVED W,FIGGIS B W,et al.Effect of dust and weather conditions on photovoltaic performance[C]//First Workshop on Smart Grid and Renewable Energy (SGRE).Doha,Qatar:SGRE,2015:1-6.
[4] 吕学梅,孙宗义,王金东,等.气象因素对光伏发电量的影响分析[C]//第31届中国气象学会年会.北京:中国气象学会,2014.
[5] 闫全全,李芬,王丽娟,等.不同季节光伏发电量与气象影响因子的诊断分析[J].上海电力学院报,2016,32(3):261-266.YAN Quanquan,LI Fen,WANG Lijuan,et al.Diagnostic analysis of the impact of meteorological factors on photovoltaic power generation in different seasons[J].Journal of Shanghai University of Electric Power,2016,32(3):261-266.
[6] 姚万祥,李峥嵘,李翠,等.各种天气状况下太阳辐射照度与太阳光照度关系[J].同济大学学报(自然科学),2013,41(5):784-787.YAO Wanxiang,LI Zhengrong,LI Cui,et al.Relationship between solar radiance and solar illuminance under all sky types[J].Journal of Tongji University(Natural Science),2013,41(5):784-787.
[7] 孙欢伟,李佳艳.积灰对光伏发电效率影响及改善[D].大连:大连理工大学,2015.
[8] 李西明,王海风.异常天气对光伏并网系统出力的影响[D].保定:华北电力大学,2017.
[9] 江敦双,张苏平,陆惟松.青岛海雾的气候特征和预测研究[J].海洋湖沼通报,2018(3):7-12.JIANG Dunshuang,ZHANG Suping,LU Weisong.The climatic characteristics and forecast study of the sea fog in Qingdao[J].Transactions of Oceanology and Limnology,2018(3):7-12.
[10] 徐华,盛立芳,柴艺淳.青岛地面太阳总辐射变化特征及影响因子分析[J].中国海洋大学学报,2014,44(5):25-31.XU Hua,SHENG Lifang,CHAI Yichun.Variation of surface total solar radiation and influencing factors in Qingdao[J].Periodical of Ocean University of China,2014,44(5):25-31.
[11] 陈菊芳,沈辉,李军勇,等.广州地区空气洁净度对光伏电站的影响[J].太阳能学报,2011,4(32):481-485.CHEN Jufang,SHEN Hui,LI Junyong,et al.The effects of air cleanliness on the PV system in Guangzhou[J].Acta Energiae Solaris Sinica,2011,4(32):481-485.
[12] 王芳超,姜雯,崔日鲜.青岛市太阳总辐射的变化特征分析[J].青岛农业大学学报(自然科学版),2014,31(4):266-271.WANG Fangchao,JIANG Wen,CUI Rixian.The analysis of characteristics of global solar radiation variation in Qingdao[J].Journal of Qingdao Agricultural University (Natural Science Edition),2014,31(4):266-271.
[13] 陈昌松,段善旭,殷进军.基于神经网络的光伏阵列发电预测模型的设计[J].电工技术学报,2009,24(9):153-158.CHEN Changsong,DUAN Shanxu,YIN Jinjun.Design of photolatic array power forecasting model based on neutral network[J].Transactions of Chinaelectrotechnical Society ,2009,24(9):153-158.
[14] 傅金洲,孙鸣.基于气候条件的光伏储能一体发电系统的能量管理策略[J].电力系统保护与控制,2018,46(24):142-149.FU Jinzhou,SUN Ming.Energy management strategy of photovoltaic energy storage integrated power generation system based on climatic conditions[J].Power System Protection and Control,2018,46(24):142-149.
[15] 朱红路,李旭,姚建曦,等.基于小波分析与神经网络的光伏电站功率预测方法[J].太阳能学报,2015,36(11):2725-2730.ZHU Honglu,LI Xu,YAO Jianxi,et al.A power forecasting method for photovoltaic power plant based on wavelet analysis and neural network[J].Acta Energia Sinica,2015,36(11):2725-2730.
[16] 朱琳琳,钟志峰,严海,等.一种新的光伏发电预测模型设计[J].太阳能学报,2016,37(1):63-68.ZHU Linlin,ZHONG Zhifeng,YAN Hai,et al.A new design of photovoltaic power generation forecasting model[J].Acta Energiae Solaris Sinica,2016,37(1):63-68.
[17] 李伟,王冰,陈献慧,等.基于气象因子权重相似日的短期光伏功率预测[J].广东电力,2018(4):59-64.LI Wei,WANG Bing,CHEN Xianhui,et al.Prediction on short-term photovoltaic power based on similar day with meteorological factor weight[J].Guangdong Electric Power,2018(4):59-64.
[18] 杨秋霞,刘同心,高辰,等.计及光伏电站功率越策的电力系统优化分析[J].电力系统保护与控制,2018,46(2):117-123.YANG Qiuxia,LIU Tongxin,GAO Chen,et al.Optimization analysis of power system considering power forecast of photovoltaic power plant[J].Power System Protection and Control,2018,46(2):117-123.
[19] LIU Y ,LI Z ,BAI K ,et al.Short-term power-forecasting method of distributed PV power system for consideration of its effects on load forecasting[J].The Journal of Engineering,2017,2017(13):865-869.
[20] GOLESTANEH F,PINSON P,GOOI H B.Very short-term nonparametric probabilistic forecasting of renewable energy generation-with application to solar energy[J].IEEE Transactions on Power Systems,2016,31(5):3850-3863.
[21] BRACALE A,CARPINELLI G,FALCO P D.A probabilistic competitive ensemble method for short-term photovoltaic power forecasting[J].IEEE Transactions on Sustainable Energy,2017,8(2):551-560.
[22] SALEH M,MEEK L,MASOUM M A S,et al.Battery-less short-term smoothing of photovoltaic generation using sky camera[J].IEEE Transactions on Industrial Informatics,2018,14(2):403-414.