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Author Haben, Stephen, author.

Title Core concepts and methods in load forecasting : with applications in distribution networks / Stephen Haben, Marcus Voss, William Holderbaum.

Publication Info. Cham : Springer, 2023.

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Location Call No. Status
 University of Saint Joseph: Pope Pius XII Library - Internet  WORLD WIDE WEB E-BOOK Springer    Downloadable
Please click here to access this Springer resource
Description 1 online resource (xv, 331 pages) : illustrations (some color)
Contents Chapter 1. Introduction -- Chapter 2. Primer on Distribution Electricity Networks -- Chapter 3. Primer on Statistics and Probability -- Chapter 4. Primer on Machine Learning -- Chapter 5. Time Series Forecasting: Core Concepts and Definitions -- Chapter 6. Load Data: Preparation, Analysis and Feature Generation -- Chapter 7. Verification and Evaluation of Load Forecast Models -- Chapter 8. Load Forecasting Model Training and Selection -- Chapter 9. Benchmark and Statistical Point Forecast Methods -- Chapter 10. Machine Learning Point Forecasts Methods -- Chapter 11. Probabilistic Forecast Methods -- Chapter 12. Load Forecast Process -- Chapter 13. Advanced and Additional Topics -- Chapter 14. Case Study: Low Voltage Demand Forecasts -- Chapter 15. Selected Applications and Examples -- Appendix.
Access Open access. GW5XE
Summary This comprehensive open access book enables readers to discover the essential techniques for load forecasting in electricity networks, particularly for active distribution networks. From statistical methods to deep learning and probabilistic approaches, the book covers a wide range of techniques and includes real-world applications and a worked examples using actual electricity data (including an example implemented through shared code). Advanced topics for further research are also included, as well as a detailed appendix on where to find data and additional reading. As the smart grid and low carbon economy continue to evolve, the proper development of forecasting methods is vital. This book is a must-read for students, industry professionals, and anyone interested in forecasting for smart control applications, demand-side response, energy markets, and renewable utilization.
Bibliography Includes bibliographical references and index.
Note Online resource; title from PDF title page (SpringerLink, viewed May 3, 2023).
Local Note Springer Nature Springer Nature - SpringerLink eBooks - Fully Open Access
Subject Electric power-plants -- Load -- Forecasting.
Electric power distribution -- Forecasting.
Electric power transmission -- Forecasting.
Electric power-plants -- Load -- Forecasting
Electric power transmission -- Forecasting
Added Author Voss, Marcus, author.
Holderbaum, William, author.
Other Form: Original 3031278518 9783031278518 (OCoLC)1369513342
ISBN 9783031278525 electronic book
3031278526 electronic book
9783031278518
3031278518
Standard No. 10.1007/978-3-031-27852-5 doi
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