摘要
在光伏发电中太阳辐照度的短期优化预测,可以有效减小辐照度对光伏发电的影响。对辐照度的短期预测,需要分析光伏发电量与气象因素间的关联性,确定模糊推理预测模型的规则数和初始参数,完成辐照度的短期预测。传统方法对太阳辐照度短期时间序列进行回归分析,按季节建立总太阳辐照度模型,但忽略了初始参数的确定,导致预测精度较低。提出基于自适应模糊推理的光伏发电中太阳辐照度短期预测模型。上述模型首先对已确定的地点,给出对应地外辐照度变化规律,利用距离分析法分析光伏发电量与气象因素间的关联性,结合自适应模糊推理理论对太阳辐照度时间序列进行建模,确定自适应模糊推理预测模型的规则数和初始参数,由此完成光伏中太阳辐照度短期预测。实验结果表明,所提模型能显著提高太阳辐照度短期预测精度,为光伏发电区间预测提供依据。
A short - term prediction model for solar irradiance in photovohaic power generation is proposed based on self - adaption fuzzy reasoning. Firstly, the change law of corresponding extraterrestrial solar irradiance for estab- lished site is provided, then the distance analytical approach is used to analyze relevance between photovohaic power productions and meteorological factors,and the model for time series of solar irradiance is carried out by combining with theory of self - adaption fuzzy reasoning. The number of rules and the initial parameters of prediction model of self - adaption fuzzy reasoning are confirmed. Finally, the short - term prediction of solar irradiance in photovohaic power generation is completed. Simulation results show that the proposed model can increase short - term prediction accuracy of solar irradiance observably and provide gist for prediction of photovoltaic power section.
作者
鲍安平
BAO An - ping(Southeast University Automation College,Jiangsu Nanjing 210096 ,China)
出处
《计算机仿真》
北大核心
2017年第10期69-72,共4页
Computer Simulation
关键词
光伏发电
太阳辐照度
短期预测
Photovoltaic power
Solar irradiance
Short - term prediction
