包含高渗透率分布式电源的母线负荷区间预测
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引用本文:张兴科,魏朝阳,李征,谭阳琛,尹积金.包含高渗透率分布式电源的母线负荷区间预测[J].电网与清洁能源,2020,36(12):101~106
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作者单位
张兴科 国家电网公司西北分部 
魏朝阳 国家电网公司西北分部 
李征 国家电网公司西北分部 
谭阳琛 国家电网公司西北分部 
尹积金 国家电网公司西北分部 
基金项目:国家电网有限公司科技项目(SGZB0000GDXX2000929)
中文摘要:针对包含高渗透率分布式电源的配电网母线负荷预测问题,不同于传统的点预测方法,提出了一种基于模糊信息粒化支持向量机的区间预测方法。采用支持向量机作为基本算法,在一定时间窗口内采用信息粒化的模型将历史数据进行粒化,将指定时间窗口内的数据采用支持向量机进行训练,并得到给定区间内的包含高渗透率分布式电源的配电网母线负荷区间预测结果。以某省会城市某110 kV母线负荷作为算例进行分析,结果表明,所提方法可以准确跟踪母线负荷在预测区间内的变化情况,对包含高渗透率分布式电源的母线负荷变化区间和趋势可以做较为精准的预测。
中文关键词:支持向量机  高渗透率分布式电源  节点负荷预测  区间预测
 
Bus Load Interval Prediction of the Distributed Generation with High Penetration
Abstract:For the bus load forecasting of the distribution network of high penetration distributed generation system, this paper proposes an interval forecasting method based on the fuzzy information granulation support vector machine to address the large error of the traditional point prediction method. The support vector machine (SVM) is used as the basic algorithm. The historical data is granulated by the information granulation model in a certain time window. The data in the specified time window is trained by using the support vector machine, and the bus load interval prediction results of the distribution network of high penetration distributed generation in a given interval is thus obtained. Taking a 110 kV bus load in a provincial capital city as an example, we have done the analysis, whose results show that the proposed method can accurately track the changes of the bus load in the prediction interval, and can accurately predict the variation range and trend of the bus load containing high penetration distributed generation.
keywords:support vector machine  high penetration distributed generation  bus load forecasting  interval forecasting
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