9789811526237-9811526230-Smart Meter Data Analytics: Electricity Consumer Behavior Modeling, Aggregation, and Forecasting

Smart Meter Data Analytics: Electricity Consumer Behavior Modeling, Aggregation, and Forecasting

ISBN-13: 9789811526237
ISBN-10: 9811526230
Edition: 1st ed. 2020
Author: Wang, Yi, Chen, Qixin, Kang, Chongqing
Publication date: 2020
Publisher: Springer
Format: Hardcover 314 pages
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Book details

ISBN-13: 9789811526237
ISBN-10: 9811526230
Edition: 1st ed. 2020
Author: Wang, Yi, Chen, Qixin, Kang, Chongqing
Publication date: 2020
Publisher: Springer
Format: Hardcover 314 pages

Summary

Acknowledged authors Wang, Yi, Chen, Qixin, Kang, Chongqing wrote Smart Meter Data Analytics: Electricity Consumer Behavior Modeling, Aggregation, and Forecasting comprising 314 pages back in 2020. Textbook and eTextbook are published under ISBN 9811526230 and 9789811526237. Since then Smart Meter Data Analytics: Electricity Consumer Behavior Modeling, Aggregation, and Forecasting textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

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 temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.


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