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文章摘要
模糊聚类-Elman神经网络短期光伏发电预测模型
Short-term photovoltaic power generation prediction model based on fuzzy clustering-Elman neural network
Received:April 04, 2019  Revised:May 28, 2019
DOI:10.19753/j.issn1001-1390.2020.12.008
中文关键词: 孤立森林  模糊C均值  Elman  BP
英文关键词: Isolation Forest  Fuzzy C Means  Elman  BP
基金项目:国家自然科学基金项目( 51507001)
Author NameAffiliationE-mail
Zhang Jinjin* Engineering Research Center of Power Quality,Ministry of Education,Anhui University 1095610420@qq.com 
Zhang Qian Engineering Research Center of Power Quality,Ministry of Education,Anhui University qianzh@ahu.edu.cn 
Ma Yuan Engineering Research Center of Power Quality,Ministry of Education,Anhui University 664328543@qq.com 
Ma Jinhui State Grid Anhui Electric Power Co,Ltd hfmajh@163.com 
Ding Jinjin State Grid Anhui Electric Power Co,Ltd Electric Power Research Institute,Ltd djinjin123@126.com 
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中文摘要:
      光伏发电功率预测是电网安全稳定运行的基础,从数据挖掘的角度提升光伏发电功率预测精度。本文提出基于孤立森林、模糊C均值和Elman的短期光伏发电功率预测模型。首先,根据预测日选择相似日数据并按天气分类作为训练样本;其次,采用孤立森林清洗训练样本中的异常部分;接着,应用模糊C均值对相似日以及待预测日的气象数据进行聚类分析。最后,结合Elman神经网络算法,形成含孤立森林数据清洗的模糊聚类-Elman神经网络的预测模型,对光伏出力进行精确预测。根据某地市现场实测数据进行实验仿真,预测结果分别与传统Elman和BP模型的预测结果进行对比,可以获得更高的预测精度。
英文摘要:
      
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