智能變電站電能質量預警系統(tǒng)研究
柏晶晶
（國網江蘇省電力公司鹽城供電公司，江蘇 鹽城 224002）
摘 要：電能質量擾動源會給電能質量帶來很大的安全隱患。提出了基于高階統(tǒng)計量的時間序列挖掘算法對異常數據進行深入分析，并結合三層四等級的預警流程，來實現對電能質量穩(wěn)態(tài)指標充分預警。實際運行結果表明，所開發(fā)的智能變電站電能質量預警系統(tǒng)能夠全面地挖掘潛在的電能質量問題，有助于促進變電運維管理水平的提升，為電網安全穩(wěn)定運行提供有力支撐。
關鍵詞：電能質量；預警；異常挖掘；偏度；峰度
中圖分類號：TM63；TM76 文獻標識碼：A 文章編號：1007-3175(2017)10-0017-04
Research on Power Quality Early Warning System for Intelligent Substation
BAI Jing-jing
（Yancheng Power Supply Company, State Grid Jiangsu Electric Power Company, Yancheng 224002, China）
Abstract: The power quality disturbance sources will bring the great potential safety hazard. This paper proposed the time sequence mining algorithm based on higher order statistics to carry out deep analysis of abnormal data and combined the three-layer four hierarchical early warning flow to realize the full early warning of power quality steady state index. The practical operation results show that the developed power quality early warning system in intelligent substation could dig the potential power quality problems roundly, which is helpful to promote the operation and maintenance management level of power transformation and provides the powerful support for the grid safe and stable operation.
Key words: power quality; early warning; anomaly detection; skewness; kurtosis
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