基于模糊双曲正切模型的短期光伏发电量预测  

The short-term photovoltaic power generation forecasting based on the fuzzy hyperbolic model

作　　者：齐红云[1] 伦淑娴[2] 

机构地区：[1]渤海大学工学院,辽宁锦州121013 [2]渤海大学新能源学院,辽宁锦州121013

出　　处：《电子设计工程》2016年第17期1-3,共3页Electronic Design Engineering

基　　金：国家自然科学基金项目(051501131);教育部-新世纪优秀人才支持计划(NCET-11-1005);2011年辽宁省第一批次科学计划项目(201402001);辽宁省自然科学基金项目(2014020143);辽宁省百千万人才工程项目(2012921061)

摘　　要：通过对影响光伏发电量产生的因素进行分析比较,在模糊双曲正切模型的基础上,建立一种光伏发电量的短期预测模型。该模型既属于模糊模型,也属于神经网络模型的范畴。可以利用其强大的学习能力,以光伏发电系统的历史数据作为训练样本,对模型进行学习,并利用得到的稳定模型对光伏发电量进行短期预测。仿真结果表明,该预测模型与其他预测方法相比有更高的预测精度。Through the analysis and comparison of the factors that affect the generation of photovoltaic power generation, the short-term prediction model of photovoltaic power generation is established based on fuzzy hyperbolic model. This model is not only a kind of fuzzy model, but also a neural network model. Using its powerful learning ability, the historical data is used as the training sample. And get the stability of the model is used for short-term forecasting of photovoltaic power generation.Simulation results show that the prediction model has higher prediction accuracy compared with other prediction methods.

关 键 词：光伏发电量 短期预测 模糊双曲正切模型 预测精度 

分 类 号：TN302[电子电信—物理电子学]