: This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied.The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and tempo ...
【目录】
Contents
1 Overview of Smart Meter Data Analytics 1
1.1 Introduction 1
1.2 Load Analysis 4
1.2.1 Bad Data Detection 5
1.2.2 Energy Theft Detection 6
1.2.3 Load Profiling 8
1.2.4 Remarks 9
1.3 Load Forecasting 11
1.3.1 Forecasting Without Smart Meter Data 11
1.3.2 Forecasting with Smart Meter Data 14
1.3.3 Probabilistic Forecasting 16
1.3.4 Remarks 18
1.4 Load Management 19
1.4.1 Consumer Characterization 19
1.4.2 Demand Response Program Marketing 21
1.4.3 Demand Response Implementation 22
1.4.4 Remarks 23
1.5 Miscellanies 25
1.5.1 Connection Verification 25
1.5.2 Outage Management 26
1.5.3 Data Compression 26
1.5.4 Data Privacy 27
1.6 Conclusions 28
References 28
2 Electricity Consumer Behavior Model 37
2.1 Introduction 37
2.2 Basic Concept of ECBM 39
2.2.1 Definition 39
2.2.2 Connotation 41
2.2.3 Denotation 42
2.2.4 Relationship with Other Models 43
2.3 Basic Characteristics of Electricity Consumer Behavior 45
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