Smart Meter Data Analytics: Electricity Consumer Behavior Modeling, Aggregation, and Forecasting (Hardcover, 2020)

Overview for Smart Meter Data Analytics.- Smart Meter Data Compression Based on Load Feature Identification.- A Combined Data-Driven Approach for Electricity Theft Detection.- GAN-based Model for Residential Load Generation.- Ensemble Clustering for Individual Electricity Consumption Patterns Extraction.- Sparse and Redundant Representation-Based Partial Usage Pattern Extraction.- Data-Driven Personalized Price Design in Retail Market Using Smart Meter Data.- Deep Learning-Based Socio-demographic Information Identification.- Cross-domain Feature Selection and Coding for Household Energy Behavior.- Clustering of Electricity Consumption Behavior Dynamics Toward Big Data Applications.- Enhancing Short-term Probabilistic Residential Load Forecasting with Quantile LSTM.- An Ensemble Forecasting Method for the Aggregated Load With Subprofiles.- Prospects of Future Research Issues on Smart Meter Data Analytics.