Graph database and graph computing for power system analysis / Renchang Dai, Guangyi Liu.

By:

Dai, Renchang

Contributor(s):

Liu, Guangyi (Scientist)

Material type: Text

TextPublisher: Hoboken, New Jersey : Wiley-IEEE Press, [2024]Description: 485 pages : illustrations ; 27 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9781119903888
9781119903871

Subject(s):

LOC classification:

TK 1005 D35 2024

Summary: "This book is a summary of cutting-edge research in graph data management and graph parallel computing on power system analysis. The authors offer extensive industry experience in designing and implementing graph computing based power system applications. The traditional relational database is replaced by graph database to model power system and implement applications at the first time. Using the graph database, the program to solve large-scale algebraic equations, high dimensional differential equations, and optimization problems is reconfigured and redesigned to accommodate graph parallel computing in this book. Graph-based nodal and hierarchical parallelism are explored to achieve high computation efficiency. The implementations of graph computing based topology analysis, state estimation, power flow, contingency analysis, security constrained automatic generation control, security constrained unit commitment, and transient simulation are demonstrated in detail."-- Provided by publisher.

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Holdings
Item type	Current library	Shelving location	Call number	Status	Date due	Barcode
Book	TUP Manila Library	Graduate Program Section-2F	GS TK 1005 D35 2024 (Browse shelf(Opens below))	Available		P00034238

Includes index.

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"This book is a summary of cutting-edge research in graph data management and graph parallel computing on power system analysis. The authors offer extensive industry experience in designing and implementing graph computing based power system applications. The traditional relational database is replaced by graph database to model power system and implement applications at the first time. Using the graph database, the program to solve large-scale algebraic equations, high dimensional differential equations, and optimization problems is reconfigured and redesigned to accommodate graph parallel computing in this book. Graph-based nodal and hierarchical parallelism are explored to achieve high computation efficiency. The implementations of graph computing based topology analysis, state estimation, power flow, contingency analysis, security constrained automatic generation control, security constrained unit commitment, and transient simulation are demonstrated in detail."-- Provided by publisher.

Description based on print version record and CIP data provided by publisher; resource not viewed.

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