摘要
针对环境温度、环境湿度、辐射强度3种影响因子,建立基于云变换的光伏出力短期预测模型。首先,利用云峰值变换将影响因子转换为论域中的定性概念。然后,通过云合并进行概念跃升,构建隶属度函数进行数据划分,结合改进的Apriori算法获取各影响因子之间的联系。最后,建立云规则发生器,对光伏发电的出力进行预测,获取在不同置信区间下的预测结果集。所建立的云变换模型,对随机性与不确定性预测更加精确,既可通过期望的形式给出预测精确值,同时也可根据云模型的不确定性原理给出指定置信度的预测范围。
In this paper,based on the knowledge of environmental temperature,environmental humidity and radiation intensity,proposes a PV output forecast model in short term,which defines a month as a cycle and an hour as a unit.Firstly,we use cloud transformation model to transformation factors into some concepts,and then combine them to less by using cloud-combination model and get the uncertainty factor. Next,we find the relationship between each factors.Finally,the rule generator is established to predict the output of photo-voltaic power generation. The cloud transformation model established in this paper is more accurate to predict the randomness and uncertainty,it can be used to predict the exact value by the expected form. At the same time,we can get the range of the prediction according to the uncertainty of cloud model by different confidence values.
作者
陈中
车松阳
Chen Zhong;Che Songyang(School of Electrical Engineering,Southeast University,Nanjing 210096,China;Jiangsu Key Laboratory of Smart Grid Technology and Equipment,Nanjing 210096,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2019年第11期3054-3061,共8页
Acta Energiae Solaris Sinica
基金
国家重点研发计划（2016YFB0101800）
国家自然科学基金（51277029）
江苏省重点研发计划（BE2015004-4）
江苏省智能电网技术与装备重点实验室课题
国家电网公司总部科技项目
