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Book Cover
E-book
Author Holderbaum, William, author

Title Energy forecasting and control methods for energy storage systems in distribution networks : predictive modelling and control techniques / William Holderbaum, Feras Alasali, Ayush Sinha
Published Cham : Springer, [2023]
©2023

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Description 1 online resource (xvi, 204 pages) : illustrations (chiefly color)
Series Lecture notes in energy, 2195-1292 ; volume 85
Lecture notes in energy ; 85. 2195-1292
Contents 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
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 Includes bibliographical references and index
Notes Online resource; title from PDF title page (SpringerLink, viewed January 12, 2023)
Subject Electric power distribution -- Automatic control
Energy storage -- Automatic control
Predictive control.
Electric power distribution -- Automatic control
Predictive control
Genre/Form Electronic books
Form Electronic book
Author Alasali, Feras, author
Sinha, Ayush, author
ISBN 9783030828486
3030828484