电测与仪表2017，Vol.54Issue(11)：36-42,7.
基于灰色关联与模糊聚类分析的负荷预处理方法
Load preprocessing method based on grey relational analysis and fuzzy clustering
摘要
Abstract
Load profiles reflect electric energy consumption of consumers, including the information of day-to-day operations and system reliability.However, some random factors such as channel errors, unexpected interruption or shutdown of power stations can result in load profiles contain abnormal data and missing values.In this paper, a load preprocessing model based on fuzzy clustering and grey relational analysis (GRA-FCM) is proposed.Firstly, the similar sample set with larger correlation degree is determined by grey correlation analysis.Then, the typical load profiles are obtained by adopting fuzzy clustering algorithm and clustering validity index.Finally, the correction is performed on the abnormal data of identification.The proposed model is applied to a city grid SCADA system, which proves the model has high accuracy and practicability.关键词
负荷预处理/灰色关联分析/模糊聚类分析/相似样本集/典型特征曲线Key words
load preprocessing/grey relational analysis/fuzzy clustering analysis/similar sample set/typical load profile分类
信息技术与安全科学引用本文复制引用
林顺富,谢潮,李东东,符杨..基于灰色关联与模糊聚类分析的负荷预处理方法[J].电测与仪表,2017,54(11):36-42,7.基金项目
国家自然科学基金资助项目(51207988) （51207988）
上海市科委科创项目(14DZ1201602) （14DZ1201602）
国家电网公司科技项目(SGRI-DL-71-14-004,52094014001Z) （SGRI-DL-71-14-004,52094014001Z）
上海绿色能源并网工程技术研究中心(13DZ2251900) （13DZ2251900）
