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Energy forecasting and control methods for energy storage systems in distribution networks (Record no. 566926)

MARC details
000 -LEADER
fixed length control field 02388 a2200265 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20231030161317.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231027b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783030828479
040 ## - CATALOGING SOURCE
Transcribing agency IIT Kanpur
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 620
Item number H711e
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Holderbaum, William
245 ## - TITLE STATEMENT
Title Energy forecasting and control methods for energy storage systems in distribution networks
Remainder of title predictive modelling and control techniques
Statement of responsibility, etc William Holderbaum, Feras Alasali and Ayush Sinha
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher Springer
Place of publication Switzerland
Year of publication 2023
300 ## - PHYSICAL DESCRIPTION
Number of Pages xvi, 204p
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Lecture notes in energy
490 ## - SERIES STATEMENT
Volume number/sequential designation ; no.85
520 ## - SUMMARY, ETC.
Summary, etc This book describes the stochastic and predictive control modelling of electrical systems that can meet the challenge of forecasting energy requirements under volatile conditions.<br/><br/>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.<br/><br/>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.<br/><br/>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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Load forecasting
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Power system
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Alasali, Feras
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Sinha, Ayush
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Home library Current library Date acquired Source of acquisition Cost, normal purchase price Full call number Accession Number Cost, replacement price Koha item type
        General Stacks PK Kelkar Library, IIT Kanpur PK Kelkar Library, IIT Kanpur 06/11/2023 2 9890.00 620 H711e A186319 13187.12 Books

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