Energy forecasting and control methods for energy storage systems in distribution networks : predictive modelling and control techniques / William Holderbaum, Feras Alasali, Ayush Sinha.
Holderbaum, William, author.; Alasali, Feras, author.; Sinha, Ayush, author.
2023
TK3070
Available Online

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Title Energy forecasting and control methods for energy storage systems in distribution networks : predictive modelling and control techniques / William Holderbaum, Feras Alasali, Ayush Sinha.
Author Holderbaum, William, author.
ISBN 9783030828486 (electronic bk.)
3030828484 (electronic bk.)
9783030828479
3030828476
DOI https://doi.org/10.1007/978-3-030-82848-6
Published Cham : Springer, [2023]
Copyright ©2023
Language English
Description 1 online resource (xvi, 204 pages) : illustrations (chiefly color).
Item Number 10.1007/978-3-030-82848-6 doi
Call Number TK3070
Dewey Decimal Classification 621.31/26
Summary This book describes the stochastic and predictive control modelling of electrical systems that can meet the challenge of forecasting energy requirements under volatile conditions. The global electrical grid is expected to face significant energy and environmental challenges such as greenhouse emissions and rising energy consumption due to the electrification of heating and transport. Today, the distribution network includes energy sources with volatile demand behaviour, and intermittent renewable generation. This has made it increasingly important to understand low voltage demand behaviour and requirements for optimal energy management systems to increase energy savings, reduce peak loads, and reduce gas emissions. Electrical load forecasting is a key tool for understanding and anticipating the highly stochastic behaviour of electricity demand, and for developing optimal energy management systems. Load forecasts, especially of the probabilistic variety, can support more informed planning and management decisions, which will be essential for future low carbon distribution networks. For storage devices, forecasts can optimise the appropriate state of control for the battery. There are limited books on load forecasts for low voltage distribution networks and even fewer demonstrations of how such forecasts can be integrated into the control of storage. This book presents material in load forecasting, control algorithms, and energy saving and provides practical guidance for practitioners using two real life examples: residential networks and cranes at a port terminal.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed January 12, 2023).
Added Author Alasali, Feras, author.
Sinha, Ayush, author.
Series Lecture notes in energy ; 85. 2195-1292
Available in Other Form Print version: 9783030828479
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Record Appears in Online Resources > Ebooks
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Introduction
Basic tools
Short term load forecasting
Control strategies in low voltage network for energy saving
Optimal control with load forecasting
Case study: Energy saving based on optimal control and load forecasts
Conclusion.

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