A Method for Detecting Outliers and Identifying Typical Power Consumption Patterns in Low-Voltage Station Area Measurement Data Based on Two-Step Cluster Analysis
Author:
Affiliation:
1. China Electric Power Research Institute Co., Ltd,Beijing,China,100192
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10649893/10651613/10652119.pdf?arnumber=10652119
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1. Classification and characterization of intra-day load curves of PV and non-PV households using interpretable feature extraction and feature-based clustering
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3. Enhancing anomaly detection accuracy and interpretability in low-quality and class imbalanced data: A comprehensive approach
4. Potential of three variant machine-learning models for forecasting district level medium-term and long-term energy demand in smart grid environment
5. Security Monitoring of IEC 61850 Substations Using IEC 62351-7 Network and System Management
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