基于SFLA和MSISSA-ANFIS的超短期光伏功率动态预测方法

李练兵; 高国强; 陶鹏; 张超; 赵莎莎; 陈伟光

doi:10.19912/j.0254-0096.tynxb.2023-0957

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (10) : 326-335. DOI: 10.19912/j.0254-0096.tynxb.2023-0957

基于SFLA和MSISSA-ANFIS的超短期光伏功率动态预测方法

李练兵¹, 高国强², 陶鹏³, 张超³, 赵莎莎³, 陈伟光²

作者信息 +

ULTRA-SHORT-TERM PV POWER DYNAMIC PREDICTION METHOD BASED ON SFLA AND MSISSA-ANFIS

Li Lianbing¹, Gao Guoqiang², Tao Peng³, Zhang Chao³, Zhao Shasha³, Chen Weiguang²

Author information +

文章历史 +

摘要

为进一步提高光伏功率预测的精度,提出一种基于SFLA、MSISSA和ANFIS的超短期光伏功率日内动态预测模型。首先针对ANFIS模型受成员函数影响较大的缺点采用MSISSA对其进行优化,并结合SFLA选取相似日的方法,构建基于SFLA和MSISSA-ANFIS的功率预测模型。然后根据相关性较高的功率、气象特征与相似日集合构建特征向量对未来4 h的光伏功率进行预测。最后将从小型气象站获得的实时更新的未来气象数据存入数据库,每隔15 min预测一次,实现光伏功率的日内动态预测。结果表明所提方法提高了超短期光伏预测的精度。

Abstract

PV power output is characterized by volatility and randomness, and accurate power prediction has important application value for safe grid operation in the process of achieving grid connection. In this paper, an intra-day dynamic prediction model of ultra-short-term PV power based on SFLA, MSISSA and ANFIS is proposed. Firstly, MSISSA is used to optimize the ANFIS model for its drawback of being influenced by the membership function, and the power prediction model based on SFLA and MSISSA-ANFIS is constructed by combining the SFLA method of selecting similar days. Then a feature vector is constructed to predict the PV power for the next 4 h based on the set of power, meteorological features and similar days with high correlation. Finally, the real-time updated future meteorological data obtained from small weather stations are stored in the database and predicted every 15 min to realize the intra-day dynamic prediction of PV power. The results show that the proposed method improves the accuracy of ultra-short-term PV prediction。

导出引用

李练兵, 高国强, 陶鹏, 张超, 赵莎莎, 陈伟光. 基于SFLA和MSISSA-ANFIS的超短期光伏功率动态预测方法[J]. 太阳能学报. 2024, 45(10): 326-335 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0957

Li Lianbing, Gao Guoqiang, Tao Peng, Zhang Chao, Zhao Shasha, Chen Weiguang. ULTRA-SHORT-TERM PV POWER DYNAMIC PREDICTION METHOD BASED ON SFLA AND MSISSA-ANFIS[J]. Acta Energiae Solaris Sinica. 2024, 45(10): 326-335 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0957

中图分类号： TM615

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